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Neural language representation models such as Bidirectional EncoderRepresentations from Transformers (BERT) pre-trained on large-scale corpora canwell capture rich semantics from plain text, and can be fine-tuned toconsistently improve the performance on various natural language processing(NLP) tasks. However, the existing pre-trained language representation modelsrarely consider explicitly incorporating commonsense knowledge or otherknowledge. In this paper, we develop a pre-training approach for incorporatingcommonsense knowledge into language representation models. We construct acommonsense-related multi-choice question answering dataset for pre-training aneural language representation model. The dataset is created automatically byour proposed "align, mask, and select" (AMS) method. We also investigatedifferent pre-training tasks. Experimental results demonstrate thatpre-training models using the proposed approach followed by fine-tuningachieves significant improvements on various commonsense-related tasks, such asCommonsenseQA and Winograd Schema Challenge, while maintaining comparableperformance on other NLP tasks, such as sentence classification and naturallanguage inference (NLI) tasks, compared to the original BERT models.
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Align, Mask and Select: A Simple Method for Incorporating
Commonsense Knowledge into Language Representation Models
Neural language representation models such as Bidirectional Encoder Representations from Transformers (BERT) can well capture rich language information from unlabelled text, and can be fine-tuned to benefit many NLP applications. However, the existing pre-trained language representation models rarely consider explicitly incorporating commonsense knowledge or other knowledge. We propose a pre-training approach for incorporating commonsense knowledge into language representation models. We construct a commonsense-related multi-choice question answering dataset for pre-training a neural language representation model. The dataset is created automatically by our proposed "align, mask, and select" (AMS) method. We also investigate different pre-training tasks. Experimental results demonstrate that pre-training models using the proposed approach followed by fine-tuning achieve significant improvements over previous state-of-the-art models on various commonsense-related tasks, such as CommonsenseQA and Winograd Schema Challenge. We also find that fine-tuned models after the proposed pre-training approach maintain comparable performance on other NLP tasks, such as sentence classification and natural language inference tasks, compared to the original BERT models. These results verify that the proposed approach, while significantly improving commonsense-related NLP tasks, does not degrade the language representation capabilities.
Align, Mask and Select: A Simple Method for Incorporating
Commonsense Knowledge into Language Representation Models
Zhi-Xiu Ye,1††thanks: Work was done during an internship at DAMO Academy, Alibaba Group. Qian Chen,2 Wen Wang,2 Zhen-Hua Ling1 1National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China 2Speech Lab, DAMO Academy, Alibaba Group [email protected], [email protected], [email protected], [email protected]
1 Introduction
Neural language representation models, such as (?; ?; ?; ?; ?; ?), can well capture rich semantics from text and consistently improve the performance of various downstream natural language processing (NLP) tasks. Bidirectional Encoder Representations from Transformers (BERT) (?), as one of the most recently developed models, has produced the state-of-the-art (SOTA) results by simple fine-tuning on various NLP tasks, including natural language inference (NLI) (?), named entity recognition (NER) (?), question answering (QA) (?; ?), text classification (?), and has achieved human-level performances on several datasets (?; ?).
However, commonsense reasoning remains a challenging task for modern machine learning methods. For example, recently (?) proposed a commonsense-related task, CommonsenseQA, and showed that the BERT model accuracy remains dozens of points lower than the human accuracy on questions about commonsense knowledge. Some examples from CommonsenseQA are shown in Part A of Table 1. As can be seen from the examples, although it is easy for humans to answer the questions based on their knowledge about the world, it is a great challenge for machines when there is limited training data.
|A) Some examples from CommonsenseQA dataset
|What can eating lunch cause that is painful?
|headache, gain weight, farts, bad breath, heartburn
|What is the main purpose of having a bath?
|cleanness, water, exfoliation, hygiene, wetness
|Where could you find a shark before it was caught?
|business, marine museum, pool hall, tomales bay, desert
|B) Some triples from ConceptNet
|(eating dinner, Causes, heartburn)
|(eating dinner, MotivatedByGoal, not get headache)
|(lunch, Synonym, dinner)
|(have bath, HasSubevent, cleaning)
|(shark, AtLocation, tomales bay)
We hypothesize that exploiting knowledge graphs (KGs) representing commonsense in QA modeling may help the model choose correct answers. For example, as shown in the Part B of Table 1, some triples from ConceptNet (?) are quite related to the questions above. Exploiting these triples in QA modeling may benefit the QA models to make the correct decision.
In this paper, we propose a pre-training approach that can leverage commmonsense KGs, such as ConceptNet (?), to improve the commonsense reasoning capability of language representation models, such as BERT, without sacrificing the language representation capabilities of the models. That is, we also aim to maintain comparable performances on other NLP tasks with the original BERT models. Note that it is challenging to incorporate the commonsense knowledge into language representation models since the commonsense knowledge is usually represented in a structured format, such as (concept, relation, concept) in ConceptNet, which is inconsistent with the data used for pre-training language representation models. For example, BERT is pre-trained on the BooksCorpus and English Wikipedia that are composed of unstructured natural language sentences.
To tackle this challenge, inspired by the distant supervision approach (?), we propose an "align, mask and select" (AMS) method that aligns a commonsense KG with a large text corpus to construct a dataset consisting of sentences with labeled concepts. Different from the the masked language model (MLM) and next sentence prediction (NSP) tasks used for pre-training BERT models, we construct a multi-choice question answering task based on the generated dataset. We then pre-train the BERT model on this dataset with the multi-choice question answering task and fine-tune it on commonsense-related tasks, such as CommonsenseQA (?) and Winograd Schema Challenge (WSC) (?). We observe significant improvements over previous SOTA results. We also fine-tune and evaluate the pre-trained models on other NLP tasks, such as sentence classification and NLI tasks in GLUE (?), and achieve comparable performance with the original BERT models.
In summary, our contributions are threefold. First, we propose a pre-training approach for incorporating commonsense knowledge into language representation models for improving the commonsense reasoning capabilities of these models. The proposed approach is applicable to BERT and other models for the fine-tuning methods. The proposed approach is applicable to various KGs, including commonsense KGs, domain-specific KGs, etc. Second, we propose an "align, mask and select" (AMS) method, inspired by the distant supervision approaches, to automatically construct a multi-choice question answering dataset and facilitate the proposed pre-training approach. Third, experiments demonstrate that the pre-trained models from the proposed approach with fine-tuning achieve significant improvement over previous SOTA models on several commonsense-related tasks, such as CommonsenseQA and Winograd Schema Challenge, and still maintain comparable performances on several sentence classification and NLI tasks on the GLUE dataset, demonstrating that the proposed pre-training approach does not degrade the language representation capabilities of the models.
2 Related Work
2.1 Language Representation Model
Language representation models have demonstrated their effectiveness for improving many NLP tasks. These approaches can be categorized into feature-based approaches and fine-tuning approaches. The early feature-based approaches include Word2Vec (?) and Glove models (?), transforming words into distributed representations. However, these methods suffered from the insufficiency of word disambiguation. (?) further proposed Embeddings from Language Models (ELMo) that derive context-aware word vectors from a bidirectional LSTM, which is trained with a coupled language model (LM) objective on a large text corpus.
The above-mentioned feature-based approaches only use the pre-trained language representations as input features for other models. In contrast, the advantage of the fine-tuning approaches is that few parameters need to be learned from scratch, after pre-training. (?) pre-trained sentence encoders from unlabeled text and fine-tuned for a supervised downstream task. (?) developed a generative pre-trained Transformer (GPT) to learn a generative language model. (?) proposed bidirectional encoder representations from transformers (BERT), which achieved the SOTA performance on a wide variety of NLP tasks. Neither feature-based nor fine-tuning language representation models have incorporated the commonsense knowledge. In this paper, we focus on incorporating commonsense knowledge into the pre-training stage of the fine-tuning approaches.
2.2 Commonsense Reasoning
Commonsense reasoning is a challenging task for modern machine learning methods. As demonstrated in recent work (?), ensembling commonsense knowledge based models with question answering models improved the commonsense reasoning ability. An alternative direction is to directly incorporate commonsense knowledge into an unified language representation model. (?) proposed to directly pre-train BERT on commonsense knowledge triples. For any triple (concept, relation, concept), they took the concatenation of concept and relation as the question and concept as the correct answer. Distractors were formed by randomly picking words or phrases in ConceptNet. In this work, we also investigate directly incorporating commonsense knowledge into an unified language representation model. However, we hypothesize that the language representations learned in (?) may be tampered since the inputs to the model constructed this way are not natural language sentences. To address this issue, we propose a pre-training approach for incorporating commonsense knowledge that includes a method to construct large-scale natural language sentences. (?) collected the Common Sense Explanations (CoS-E) dataset using Amazon Mechanical Turk and applied a Commonsense Auto-Generated Explanations (CAGE) framework to language representation models, such as GPT and BERT. However, collecting this dataset used a large amount of human efforts. In contrast, we propose an "align, mask and select" (AMS) method, inspired by the distant supervision approaches, to automatically construct a multi-choice question answering dataset.
2.3 Distant Supervision
The distant supervision approach was originally proposed for generating training data for the relation classification task. The distant supervision approach (?) assumes that if two entities/concepts participate in a relation, all sentences that mention these two entities/concepts express that relation. Note that it is inevitable that there exists noise in the data labeled by distant supervision (?). In this paper, instead of employing the relation labels labeled by distant supervision, we focus on the aligned entities/concepts. We propose the AMS method to construct a multi-choice QA dataset that aligns sentences with commonsense knowledge triples, masks the aligned words (entities/concepts) in sentences and treat the masked sentences as questions, and selects several entities/concepts from knowledge graphs as distractor choices.
3 Commonsense Knowledge Base
We use ConceptNet11 1 https://github.com/commonsense/conceptnet5/wiki (?), one of the most widely used commonsense knowledge bases. ConceptNet is a semantic network that represents the large sets of words and phrases and the commonsense relationships between them (36 core relations). It contains over 21 million edges and over 8 million nodes. Its English vocabulary contains approximately 1,500,000 nodes. And it contains at least 10,000 nodes for each of the 83 languages, respectively.
Each instance in ConceptNet can be represented as a triple = (concept, relation, concept), indicating relation between the two concepts concept and concept. For example, the triple (semicarbazide, IsA, chemical compound) means that "semicarbazide is a kind of chemical compounds"; the triple (cooking dinner, Causes, cooked food) means that "the effect of cooking dinner is cooked food", etc.
|(1) A triple from ConceptNet
|(population, AtLocation, city)
|(2) Align with the English Wikipedia dataset to obtain a sentence containing "population" and "city"
|The largest city by population is Birmingham, which has long been the most industrialized city.
|(3) Mask "city" with a special token "[QW]"
|The largest [QW] by population is Birmingham, which has long been the most industrialized city?
|4) Select distractors by searching (population, AtLocation, ) in ConceptNet
|(population, AtLocation, Michigan)
|(population, AtLocation, Petrie dish)
|(population, AtLocation, area with people inhabiting)
|(population, AtLocation, country)
|5) Generate a multi-choice question answering sample
|question: The largest [QW] by population is Birmingham, which has long been the most industrialized city?
|candidates: , Michigan, Petrie dish, area with people inhabiting, country
4 Constructing Pre-training Dataset
We first filter the triples in ConceptNet as follows: (1) Filter triples in which one of the concepts is not English words. (2) Filter triples with the general relations "RelatedTo" and "IsA", which hold a large proportion in ConceptNet. (3) Filter triples in which one of the concepts has more than four words or the edit distance between the two concepts is less than four. After filtering, we obtain 606,564 triples.
Each training sample is generated by three steps: align, mask and select, which is denoted the AMS method. Each sample in the dataset consists of a question and five candidate answers, which has the same form as the CommonsenseQA dataset. An example of constructing one training sample by masking concept is shown in Table 2.
Firstly, we align each triple (concept, relation, concept) in the filtered triple set to the English Wikipedia dataset to extract the sentences containing the two concepts. Secondly, we mask the concept or concept in one sentence with a special token [QW] and treat this sentence as a question, where QW is a replacement word of the question words "what", "where", etc. And the masked concept or concept is the correct answer for this question. Thirdly, for generating the distractors, (?) formed distractors by randomly picking words or phrases in ConceptNet. In our work, in order to generate more confusing distractors than the random selection approach, we select distractors sharing the same other unmasked concept, i.e., concept or concept, and the same relation with the correct answer. That is to say, we search (, relation, concept) or (concept, relation, ) in ConceptNet to select the distractors, where is a wildcard character that can match any word or phrase. For each question, we reserve four distractors and one correct answer. If there are less than four matched distractors, we discard this question instead of complementing it with random selection. If there are more than four distractors, we randomly select four distractors from them. After applying the AMS method, we create 16,324,846 multi-choice question answering samples.
5 Pre-training BERT_CS
We investigate a multi-choice QA task for pre-training the English BERT base and BERT large models released by Google22 2 https://github.com/google-research/bert on our constructed dataset. The resulting models are denoted BERT_CS and BERT_CS, respectively. We then evaluate the performance of fine-tuning the BERT_CS models on several NLP task (Section 6).
To reduce the large cost of training BERT_CS models from scratch, we initialize the BERT_CS models (for both BERT and BERT models) with the parameter weights released by Google. We concatenate the question with each candidate to construct a standard input sequence for BERT_CS (i.e., "[CLS] the largest [QW] by … ? [SEP] city [SEP]", where [CLS] and [SEP] are two special tokens), and the hidden representations over the [CLS] token are run through a softmax layer to predict whether the candidate is the correct answer.
|WSC Task
|CoS-E (?)
The objective function is defined as follows:
where is the correct answer, the parameters in the softmax layer, N the total number of candidates, and the vector representation of the special token [CLS]. We pre-train BERT_CS models with the batch size 160, the initial learning rate , and the max sequence length 128 for 1 epoch. Pre-training is conducted on 16 NVIDIA V100 GPU cards with 32G memory for about 3 days for the BERT_CS model and 1 day for the BERT_CS model.
|LM ensemble
|Knowledge Hunter
6 Experiments
In the first set of experiments, we fine-tune the BERT_CS models on several commonsense-related NLP tasks to investigate whether the proposed approach improves the commonsense reasoning capability. In the second set of experiments, we evaluate the BERT_CS models on other NLP tasks, such as text classification and natural language inference (NLI), to investigate whether the proposed approach maintains the general language representation capabilities.
Note that when fine-tuning on the commonsense-related, multi-choice QA tasks, e.g., CommonsenseQA and Winograd Schema Challenge, we fine-tune all parameters in BERT_CS, including the last softmax layer from the token [CLS]; whereas for the second set of experiments, we randomly initialize the classifier layer and train it from scratch. Additionally, as described in (?), sometimes fine-tuning on BERT is observed to be unstable on small datasets. Hence we run experiments with 5 different random seeds and select the best model based on the development set for all of the fine-tuning experiments in this section.
6.1 CommonsenseQA
The CommonsenseQA dataset consists of 12,247 questions with one correct answer and four distractor answers. This dataset consists of two splits, the question token split and the random split. Our experiments are conducted on the more challenging random split, which is the main evaluation split according to (?). The statistics of the CommonsenseQA dataset are summarized in Table 3.
Same as the pre-training stage, the input data for fine-tuning the BERT_CS models is formed by concatenating each question-answer pair as a sequence. The hidden representations over the [CLS] token are run through a softmax layer to create the predictions. The objective function is the same as Equations 1 and 2. We fine-tune the BERT_CS models on CommonsenseQA for 2 epochs with a learning rate of 1e-5 and a batch size of 16.
Table 4 shows the accuracy on the CommonsenseQA test set from the baseline BERT models, the previous SOTA model CoS-E (?), and our BERT_CS models. CoS-E model requires a large amount of human effort to collect the Common Sense Explanations (CoS-E) dataset. In comparison, our multi-choice question-answering dataset is constructed automatically. The BERT_CS models significantly outperform the baseline BERT models with BERT_CS achieving a 5.5% absolute gain over the baseline BERT model and a 4.0% absolute gain over the previous SOTA CoS-E model.
6.2 Winograd Schema Challenge
The Winograd Schema Challenge (WSC) (?) is introduced for testing AI agents for commonsense knowledge. The WSC consists of 273 instances of the pronoun disambiguation problem. For example, for sentence "The delivery truck zoomed by the school bus because it was going so fast." and a corresponding question "What does the word it refers to?", the machine is expected to answer "delivery truck" instead of "school bus". On this task, we follow (?) and employ the WSCR dataset (?) as the extra training data. The WSCR dataset is split into a training set of 1,322 examples and a test set of 564 examples. We use the training set for fine-tuning and the test set for validating BERT_CS models, respectively, and test the fine-tuned BERT_CS models on the WSC dataset.
We transform the pronoun disambiguation problem into a multi-choice question answering problem. We mask the pronoun word with a special token [QW] to construct a question, and put the two candidate phrases as candidate answers. The remaining procedures are the same as the CommonsenseQA task. We use the same loss function as (?), that is, if c is correct and c is not, the loss is
where follows Equation 2 with , and are hyper-parameters. Similar to (?), we search and by optimizing the accuracy on the WSCR test set (i.e., the development set for the WSC data set). We set the batch size 16 and the learning rate . We evaluate our models on the WSC dataset and its various partitions described in (?). We also evaluate the fine-tuned BERT_CS model (without using the WNLI training data for further fine-tuning) on the WNLI test set, one of the GLUE tasks (?). We first transform the examples in WNLI from the premise-hypothesis format into the pronoun disambiguation problem format (?) and then transform it into the multi-choice QA format.
|Source Data
|Wikipedia and ConceptNet
|Wikipedia and ConceptNet
|Wikipedia and ConceptNet
|Wikipedia and ConceptNet
The results on the WSC dataset and its various partitions and the WNLI test set are shown in Table 5. Note that the results for (?) are fine-tuned on the whole WSCR dataset, including its training and test set partitions. Results for LM ensemble (?) and Knowledge Hunter(?) are cited from (?). Results for "BERT + MTP" is taken from (?) as the baseline of applying BERT to the WSC task. As can be seen from Table 5, the "BERT + MCQA" achieves better performance than "BERT + MTP" on four of the seven evaluation criteria and achieves significant improvements on the assoc. and consist. partitions, which demonstrates that MCQA is a better problem formatting method than MTP for the WSC task. Also, our "BERT_CS + MCQA" achieves the best performance on all of the evaluation criteria except consist.33 3 Knowledge Hunter achieves better performance on consist. by a rule-based method (?)., and achieves a 3.3% absolute improvement on the WSC dataset over the previous SOTA results from (?).
The General Language Understanding Evaluation (GLUE) benchmark (?) is a collection of diverse natural language understanding tasks, including single-sentence tasks CoLA and SST-2, similarity and paraphrasing tasks MRPC, STS-B and QQP, and natural language inference tasks MNLI, QNLI, RTE and WNLI.
To investigate whether our multi-choice QA based pre-training approach can maintain the performance on common text classification tasks, we evaluate the BERT_CS models on 8 GLUE datasets and compare the performance with the baseline BERT models. Following (?), we use the batch size 32 and fine-tune for 3 epochs for all GLUE tasks, and select the fine-tuning learning rate among 1e-5, 2e-5, and 3e-5 based on the performance on the development set. Results are presented in Table 6. We observe that the BERT_CS model achieves comparable performance with the BERT model and the BERT_CS model achieves slightly better performance than the BERT model. We hypothesize that the commonsense knowledge may not be required for GLUE tasks. On the other hand, these results demonstrate that our proposed pre-training approach does not degrade the sentence representation capabilities of BERT models.
|1) Dan had to stop Bill from toying with the injured bird. [He] is very compassionate.
|2) Dan had to stop Bill from toying with the injured bird. [He] is very cruel.
|3) The trophy doesn't fit into the brown suitcase because [it] is too large.
|4) The trophy doesn't fit into the brown suitcase because [it] is too small.
7 Analysis
7.1 Pre-training Strategy
We conduct several experiments comparing different data and different pre-training tasks on the BERT model. For simplicity, we discard the subscript in this subsection.
The first set of experiments is to compare the efficacy of our data creation approach versus the data creation approach in (?). First, same as (?), we collect 606,564 triples from ConceptNet, and construct 1,213,128 questions, each with a correct answer and four distractors. This dataset is denoted the TRIPLES dataset. We pre-train BERT models on the TRIPLES dataset with the same hyper-parameters as the BERT_CS models and the resulting model is denoted BERT_triple. We also create several model counterparts based on our constructed dataset:
Distractors are formed by randomly picking concept or concept in ConceptNet instead of those sharing the same concept or concept and the same relation with the correct answers. We denote the resulting model from this dataset BERT_CS_random.
Instead of pre-training BERT with a multi-choice QA task that chooses the correct answer from several candidate answers, we mask concept and concept and pre-train BERT with a masked language model (MLM) task. We denote the resulting model from this pre-training task BERT_MLM.
We randomly mask 15% WordPiece tokens (?) of the question as in (?) and then conduct both multi-choice QA task and MLM task simultaneously. The resulting model is denoted BERT_CS_MLM.
All these BERT models are fine-tuned on the CommonsenseQA dataset with the same hyper-parameters as described in Section 6.1 and the results are shown in Table 7. We observe the following from Table 7.
Comparing model 1 and model 2, we find that pre-training on ConceptNet benefits the CommonsenseQA task even with the triples as input instead of sentences. Further comparing model 2 and model 6, we find that constructing natural language sentences as input for pre-training BERT performs better on the CommonsenseQA task than pre-training using triples. We also conduct more detailed comparisons between fine-tuning model 1 and model 2 on GLUE tasks. The results are shown in Table 6. BERT_triple yields much worse results than BERT and BERT_CS, demonstrating that pre-training directly on triples may hurt the sentence representation capabilities of BERT.
Comparing model 3 and model 6, we find that pre-training BERT benefits from a more difficult dataset. In our selection method, all candidate answers share the same (concept, relation) or (relation, concept), that is, these candidates have close meanings. These more confusing candidates force BERT_CS to distinguish synonym meanings, resulting in a more powerful BERT_CS model.
Comparing model 5 and model 6, we find that the multi-choice QA task works better than the masked LM task as the pre-training task for the target multi-choice QA task. We hypothesize that, for the masked LM task, BERT is required to predict each masked wordpiece (in concepts) independently; whereas, for the multi-choice QA task, BERT is required to model the whole candidate phrases. In the latter way, BERT is able to model the whole concepts instead of paying much attention to the single wordpieces in the sentences. Comparing model 4 and model 6, we observe that adding the masked LM task hurts the performance of BERT_CS. This is probably because the masked words in questions may have a negative influence on the multi-choice QA task. Finally, our proposed model BERT_CS achieves the best performance on the CommonsenseQA development set among these different models.
7.2 Performance Curve
We investigate the performance curve on the CommonsenseQA development set from BERT_CS against the pre-training steps. For every 10,000 training steps, we save the model as the initial model for fine-tuning. For each of these models, we run experiments for 10 times with random restarts, that is, we use the same pre-trained checkpoint but perform different fine-tuning data shuffling. Due to the unstability of fine-tuning BERT (?), we remove the results that are significantly lower than the mean. In our experiments, we remove the accuracy lower than 0.57 for BERT_CS and 0.60 for BERT_CS. The mean and standard deviation values are plotted in Figure 1. We observe that the performance of BERT_CS converges around 50,000 training steps and BERT_CS may not have converged at the end of the pre-training stage, which demonstrates that BERT_CS is more powerful at incorporating commonsense knowledge. We also compare with pre-training BERT_CS models for 2 epochs. However, pre-training for 2 epochs produces worse performance, probably due to over-fitting. Pre-training on a larger corpus (with more QA samples) may benefit the BERT_CS models and we leave this investigation to the future work.
7.3 Error Analysis
Table 8 shows several cases from the WSC dataset. Questions 1 and 2 only differ in the words "compassionate" and "cruel". BERT_CS chooses correct answers for both questions while BERT chooses the same choice "Bill" for both questions. We hypothesize that BERT tends to choose the closer candidates. To investigate this hypothesis, we split the WSC test set into CLOSE and FAR subsets, based on whether the correct answer is closer or farther to the pronoun in the sentence than another candidate. We find that BERT_CS achieves the same 82.4% accuracy on the CLOSE set as BERT and significantly better accuracy on the FAR set than BERT (68.6% versus 60.6%), demonstrating that BERT_CS is probably less influenced by proximity and more focused on semantics.
Questions 3 and 4 only differ in the words "large" and "small". However, neither BERT_CS nor BERT chooses the correct answers. We hypothesize that since "suitcase is large" and "trophy is small" are probably quite frequent in the pre-training text, both BERT and BERT_CS models make mistakes. In future work, we will investigate other approaches for overcoming the sensitivity of language models and further improving commonsense reasoning.
8 Conclusion
In this paper, we develop a pre-training approach for incorporating commonsense knowledge into language representation models such as BERT. We construct a commonsense-related multi-choice question answering dataset for pre-training BERT. The dataset is created automatically by our proposed "align, mask, and select" (AMS) method. Experimental results demonstrate that pre-training using the proposed approach followed by fine-tuning significantly outperforms previous SOTA models on commonsense-related CommonsenseQA and Winograd Schema Challenge tasks, while maintaining comparable performance on other NLP tasks, such as sentence classification and NLI tasks, compared to the original BERT models. In future work, we will investigate the efficacy of the proposed approach in exploiting other structured knowledge graphs such as Freebase (?) for NLP tasks. We also plan to incorporate commonsense knowledge information into other language representation models such as the BERT model with whole word masking, XLNet (?), and RoBERTa (?).
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- [Sang and De Meulder 2003] Sang, E. F., and De Meulder, F. 2003. Introduction to the conll-2003 shared task: Language-independent named entity recognition. arXiv preprint cs/0306050.
- [Speer, Chin, and Havasi 2017] Speer, R.; Chin, J.; and Havasi, C. 2017. Conceptnet 5.5: An open multilingual graph of general knowledge. In Thirty-First AAAI Conference on Artificial Intelligence.
- [Sun et al. 2019] Sun, K.; Yu, D.; Yu, D.; and Cardie, C. 2019. Probing prior knowledge needed in challenging chinese machine reading comprehension. arXiv preprint arXiv:1904.09679.
- [Talmor et al. 2018] Talmor, A.; Herzig, J.; Lourie, N.; and Berant, J. 2018. Commonsenseqa: A question answering challenge targeting commonsense knowledge. arXiv preprint arXiv:1811.00937.
- [Trichelair et al. 2018] Trichelair, P.; Emami, A.; Cheung, J. C. K.; Trischler, A.; Suleman, K.; and Diaz, F. 2018. On the evaluation of common-sense reasoning in natural language understanding. arXiv preprint arXiv:1811.01778.
- [Trinh and Le 2018] Trinh, T. H., and Le, Q. V. 2018. A simple method for commonsense reasoning. arXiv preprint arXiv:1806.02847.
- [Wang et al. 2018] Wang, A.; Singh, A.; Michael, J.; Hill, F.; Levy, O.; and Bowman, S. R. 2018. Glue: A multi-task benchmark and analysis platform for natural language understanding. arXiv preprint arXiv:1804.07461.
- [Wu et al. 2016] Wu, Y.; Schuster, M.; Chen, Z.; Le, Q. V.; Norouzi, M.; Macherey, W.; Krikun, M.; Cao, Y.; Gao, Q.; Macherey, K.; et al. 2016. Google's neural machine translation system: Bridging the gap between human and machine translation. arXiv preprint arXiv:1609.08144.
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12 Lead ECG
The 12-lead ECG is usually performed over a few minutes whilst the patient is laying down. By monitoring the conduction waveforms of the heart from a variety of viewpoints, it is possible to assess any resting abnormality likely to indicate heart disease.
The ECG may provide information on excess thickening of the heart wall, current or previous heart attacks, conduction defects, and abnormal rhythms. It may also be used to diagnose electrolyte imbalance and assess medication therapy.
It is less useful for occasional arrhythmia as the chances of the patient having an event during a short test is often very low. It is also of little use for coronary artery disease as the patient is at rest and therefore unlikely to suffer an ischaemic episode.

subset: commoncrawl


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- Excel Invoice Template 1.60
Version: 1.60
Released: 2012-10-17 18:36:16
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Released: 2012-10-17 18:36:16
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Excel Invoice Template 1.60 Description
This is a free Excel Invoice Template that provides a Fill In The Blank invoice form and is capable of calculating and creating invoices. Its what-you-see-is-what-you-get invoice form provides simple yet effective invoice software for small businesses. If you know how to use Microsoft Excel, you know how to use Excel Invoice Template.
The invoice template is customizable, since it is based on Microsoft Excel. For example, you can easily change the text fonts, styles, colors of the template, by using various tools provided by Excel.
The invoice template shows quantity, description, unit price, taxable status, and amount per line. Sub-total, tax and total amount are computed from the line items automatically. You can even provide or insert a logo image for your invoice form to make your invoices look more professional.
As a freelancer or small business owner, you may not need a fully featured invoicing program such as Excel Invoice Manager. This free invoice template offers a budget-friendly invoicing system, and it helps you to create professional-looking invoices.
This invoice template is for general business. Click the link on the invoice form to find more - for example, there are general-purpose service invoice template, vat invoice template, invoice template that charges GST Tax on shipping cost, invoice template that shows special symbol for gift or free items, packing list or packing slip template, invoice Form with fixed or static product / service items, invoice templates with discount column, invoice template and receipt template for jeweler shop / gold shop, invoice template for newsletter publishing service, job invoice template with job address, start date, finish date and description, engineering service invoice template with support for change order, web hosting service invoice template with payment slip, two-column service invoice template for plumbing and heating service company, invoice template with "City, State ZIP" in Holland format.
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Santa Maria Taco Shells x12 135g/ Tacos
ENCrispy roasted corn tacos to make your Mexican tacos at home. Enjoy its taste and crisp texture. SVRostad krispig majs taco för dig att göra ditt hem mexikanska tacos. Njuta av smaken och skarpa konsistens.
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ENCorn flour, sunflower oil, canola oil, salt. SVMajsmjöl , solrosolja , rapsolja , salt.
ENFlour or mixture for the preparation of the famous original apple pie. Enjoy an ideal time in the kitchen with the elaboration of one of the most classic cakes in international cuisine. NLMeel of het mengsel voor de bereiding van de beroemde appeltaart origineel. Geniet van een ideaal in de keuken met de ontwikkeling van een van de meest klassieke...
ENPrepare your shoarma with this mix of spices and thin strips of meat. Add it into pita bread with vegetables, onion, yogurt sauce and garlic sauce. A specialty that you can prepare at home so easily. NLBereid je shoarma voor met deze mix van kruiden en dunne reepjes vlees. Voeg het toe aan pitabrood met groenten, ui, yoghurtsaus en knoflooksaus. Een...
ENUse peppermint for soups, legumes, pasta and lamb. If you add a pinch of peppermint to the fresh cheese or tomatoes with olive oil you will discover how it enriches the natural flavor of everything. ESUtiliza la hierbabuena para sopas, legumbres, pastas y cordero. Si añades una pizca de hierbabuena al queso fresco o a tomates con aceite de oliva...
ENTurmeric is used to enrich or color rice, eggs and salads. In addition, turmeric has numerous properties for your health. This spice has 10 anticancer bodies, helps to reduce cholesterol and its stimulating components favor the nervous system and it affects the immune system positively. ESLa cúrcuma se usa para enriquecer o dar color a arroces, huevos y...
ENCarmencita's Garlic powder. Mix a teaspoon of garlic powder with a little white wine and add it to your main course, you'll love it! Enrich your fish or meat dishes and sauces. ESAjo en polvo de la marca Carmencita. Mezcla una cucharadita de ajo en polvo con un poco vino blanco y añádelo a tu plato principal, te encantará! Enriquece así tus platos de...
ENDo you have a party? A visit? Offer them a different snack with these crunchy Gwoon peanuts. Coated with a crunchy and edible shell full of flavor, with a touch of garlic and spices that will make the peanuts are no longer the same. NLHeb je een feestje? Een bezoek? Bied ze een andere snack aan met deze knapperige Gwoon-pinda's. Gecoat met een...
ENDevos & Lemmens mayonnaise is creamy and with a unique flavor. This is made with eggs and comes in a handy container so you can easily serve yourself. Perfect to accompany meats, fish and fried. Try it! NLDevos & Lemmens-mayonaise is romig en met een unieke smaak. Dit is gemaakt met eieren en wordt geleverd in een handige container, zodat je...
ENNapikol is grown in cold climates and its best season is autumn. Usually consumed in stews, broths, cooked or accompanying other vegetables. They have a lot of water, fiber, carbohydrates and few calories, they are rich in vitamin C and minerals.
ENBatchelor's instant noodles come in a multitude of different flavors and today we present the curry flavors. Some tender noodles, with a rich and tasty sauce that you will love, they are also very easy to make and in 5 minutes you will have a hot, rich and tasty dish for you to eat just as quickly and you can continue doing those important things that...
ENRobertson's Golden Shred is delicious flavored orange marmalade. Take it with toast for breakfast and start the day with joy. It is suitable for vegetarians and vegans.
ENIntense sauce Rogan Josh of intermediate spicy. This sauce is an exquisite mixture of tomatoes, onions, peppers and roasted spices. It is totally suitable for vegetarians, celiacs and contains neither coloranets nor artificial aromas.
ENOriental noodles are a quick way to enjoy a hot and quick dish. Batchelor's knows that sometimes we don't like to cook for hours and that is why it brings us its range of instant oriental noodles with different flavors. This is Barbecue flavor so you can enjoy the authentic flavor of roast meat, spices, sauces ... all in one! Try them out!
ENThe Olde English Marmalade is made from thick cut oranges. It stands out for its intense citrus flavor. It is ideal for breakfast and totally suitable for vegetarians.
ENTony's Chocolonely love parties and create chocolates according to them so this Christmas, why not try their chocolate with Christmas Wine flavor? A delicious drink made with wine and spices now in the form of a chocolate tablet to enjoy it in mouthfuls! Hurry up to try it! NLTony's Chocolonely is dol op feestjes en maakt volgens hen chocolaatjes, dus...
ENIt is prepared for doughnut balls or Oliebollen as they are called in the Netherlands, it is easy to use. You have everything you need to prepare this typical sweet just have to add a couple of eggs, water and love for cooking! Surprise everyone with this delicious sweet and enjoy a fun and delicious after-dinner! NLHet is bereid voor donutballen of...
ENSoluble coffee 100% natural with its classic and powerful original aroma. It has an approximate capacity of 100 cups. DELöslicher Kaffee 100% natürlich mit seinem klassischen und kraftvollen Originalaroma. Es hat eine ungefähre Kapazität von 100 Tassen.
ENSweet typical Indian pickle of aubergine or eggplant with spices. The level of spiciness is medium and is known in India as Brinjal Pickle. Discover the best flavor of the aubergine with exotically sweet touches.
ENThis dense Korma sauce is exquisite. A fusion of spices, oils and coconut, which will conquer your stomach. Prepare a typical Korma meal with a little basmati rice and a mixture of vegetables with chicken.
ENMcVitie's ginger cookies have a delicious flavor, ginger gives a touch of citrus and a little spicy that will make you enjoy all the nuances of this spice. Enjoy these cookies with a cup of tea and you will notice how their aromas and flavors are accentuated.
ENDelicious and extra soft pink and white marshmallows. They do not contain artificial colors or flavors. They are the favorites of both children and adults. DELeckere und extra weiche rosa und weiße Marshmallows. Sie enthalten keine künstlichen Farb- oder Aromastoffe. Sie sind die Favoriten von Kindern und Erwachsenen.
ENDelightful black tea Earl Gray with the fragant flavour of bergamot and lemon. Prepare your tea by heating the water for 2 minutes, 3 minutes if you want a stronger flavor. You can add some milk or drink it as it is, it's very good. This package contains 50 tea bags.
ENDelicious Beinz or Heinz baked beans in tomato sauce. They have a high protein content, lots of fiber and few fats. It also contains no added sugar, but has a natural sweetener. It stands out for having less salt than the usual beans. Beans with tomato are a typical English dish that will give you the energy to eat the world. Open the can and go for them.
ENTry the exquisite fusion of parsley, chives, garlic and pepper to give the best natural flavor to your salad. Discover a new way of dressing salads with Knorr. One pack contains 5 sachets. To prepare it you only have to add 3 tablespoons of water and 3 tablespoons of olive oil with the contents of the sachet. DEProbieren Sie die exquisite Mischung aus...
ENDress your salads with the Hellmann's Caesar Dressing and enjoy with the perfect combination of flavors that will make your salads something to dream about.
ENIf you like latte coffee with a touch of caramel you will love this Nestlé Gold instant coffee. Prepare your own Caramel Latte Coffee in a few minutes in the comfort of your home or at work. This package contains 8 individual sachets. DEWenn Sie Lattekaffee mit einem Hauch Karamell mögen, werden Sie diesen Nestlé Gold Instantkaffee lieben. Bereiten Sie...
ENBlue Dragon high quality coconut milk, cook your exotic Indian or Oriental dishes with this seasoning. Coconut milk is also used to make some cocktails, would you try it?
ENEnjoy the best chili con carne with this spectacular spicy salsa with chiles and beans specially made for this Mexican dish. Its ingredients are 100% natural and have an approximate capacity for 4 servings.
ENEnjoy a galaxy of chocolate at your breakfast! Delicious chocolate stars to start the day with energy and fun. Doves Farm cereals are gluten free so the whole family can enjoy its chocolate flavor out of this world!
ENWho does not want a good plate of soup on a cold day? Everyone, right? Well now we offer you this tomato soup with pieces of Amy's Kitchen. A delicious soup with authentic pieces of tomato, made with ingredients of organic origin and gluten-free, low in calories and suitable for vegetarians, it has it all! You just have to try it, what are you waiting for?
ENGlazed cherries are perfect to give that special touch to your desserts such as cakes, ice cream, puddings or yogurts. Enjoy a sweet bite, full of flavor and we are sure that all members of your family will love it. Coop offers you a quality and delicious product.


text: Choosing a daycare or preschool feels like one of the biggest decisions you'll ever make. In some ways, it is! You're putting your toddler's well-being and academic future in the hands of others. It's a nerve-wracking and overwhelming proposition, to say the least. Beyond that, there are SO many choices and philosophies out there. How do you know which early childhood education philosophy is right for your kid? In this Curriculum Comparison series, I'm going to do my best to break them all down for you and give you the information you need to make the right decision for your family. In this article, we'll go into Waldorf vs Montessori.


text: Name: Kaneko MBR Demo(s): Spoiler: Some Art Examples! Current Rank-Points: Diamond | 212 Character Biographies (Optional): N/A Hitlist (Optional): Everyone who do art >:3c Availability: Still working on some commission! Will be available once is done! Season Record (Season 1): - End of Season Rank-Points: 0 Season High Rank-Points: 0 Battle Record: ART MBR Vs. Hunter ( WIN ) MBRQ Points: 3


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Website Under Construction PHP ScriptAdd a very beautiful very high-quality Coming Soon landing page to your website while it is developed. Average rating of 5 based on 1 votes
This PHP script helps you quickly add a very beautiful very high-quality "Coming Soon" landing page to your website while it's being developed.
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|.php, .css, .html, Javascript .js
|admin, page, twitter, responsive, SCRIPT, modern, Slide, progress, spam, email, contact, coming soon, build, construction, subscribe


text: There's nothing like having the tools to do a job properly. Our W350 has just returned from a Concrete Profiling Job inside a factory, profiling the floor. The machine was used to remove high spots prior to tiling enabling the client to achieve the correct "fall" for water drainage. The process started by bulking out the concrete with the standard milling drum (15mm lacing), then once we achieved the correct levels we replaced the standard drum and installed our Micro-Milling Drum (4mm lacing). You can see by the attached picture what the Micro-Drum will achieve. This machine can also be used for line removal, raised audible line removal or the accurate milling around services or cutting of chases for the asphalt crew


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November 15, 2017
Iranian Ships Seized 'Smuggling North Korean Machine Guns to Somalia Militants' – Somalia, Iran, and North Korea
North Korean weapons were seized aboard Iranian smuggling ships as authorities seek to stamp out smuggling, a UN report has revealed. The weapons were on their way to war-torn Somalia when they were caught by an inspection looking for contraband. A UN diplomat earlier asked: "Why are Iranian and North Korean small arms finding their way into Somalia from Libya? Do they date from before the arms embargoes (against both North Korea and Iran)? How did they get there from Libya? The ships were intercepted in the Arabian Sea by a French vessel. The Type 73 machine guns were manufactured in the prison country before being sold to Iran between 1970 and 1980.
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Chinese Cameras Monitor US Army Bases, Streets and Homes – United States
Hangzhou Hikvision Digital Technology, in which the Chinese government has a 42% share, produces surveillance equipment for China's vast domestic surveillance network, used to keep tabs on the Chinese people. But, these cameras are also being used to monitor U.S. Army bases, embassies, streets, and homes. Hikvision cameras hang at Fort Leonard Wood in Missouri, where U.S. troops conduct basic training and exercises for nuclear and biochemical defense. The company's equipment was also installed at the U.S. Embassy in Kabul, Afghanistan. Hikvision has been providing the Memphis police department with security cameras for a decade, and the company also sells models for consumer use in U.S. homes and offices. "The fact that it's at a U.S. military installation and was in a very sensitive U.S. embassy is stunning," Carolyn Bartholomew, chairwoman of the U.S.-China Economic and Security Review Commission, told the WSJ, adding, "We should not presume that there are benign intentions in the use of information-gathering technology that is funded directly or indirectly by the Chinese government." This past summer, the Department of Homeland Security issued a cybersecurity warning for Hikvision, noting the existence of a loophole in the system that easily allows hackers, including state-owned hackers, to breach the system. Hikvision is no longer on the list of automatically approved suppliers, according to the General Services Administration, and several security vendors are reportedly either refusing to carry Hikvision products or restricting their purchase for fear that the surveillance equipment could be used to spy on Americans.
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Great Plains Methodist Conference to Hold Active Shooter Training – Kansas, United States
The Great Plains United Methodist Conference will be holding an active shooter training in Wichita next month. It's in response to the many questions they've been receiving after the recent church shooting in Sutherland Springs, Texas. Hollie Tapley, disaster response coordinator for the Great Plains United Methodist Conference, says when she got to her office the Monday morning after the shooting, her email inbox was full of people with questions. "Within a 30-minute period of time I had 12 churches that were wanting a training," she says. The training is open to the public and will also be live streamed on Wichita's Chapel Hill United Methodist Church website.
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To sign up for the complete daily G4S Corporate Risk Services Intelligence Bulletin, as well as regular intelligence and risk updates and news, click here to subscribe!
If you need immediate assistance from G4S Corporate Risk Services or would like to learn more about our services, email firstname.lastname@example.com or call 800.275.8310.


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Omega-3 shown to protect against heart disease-related death, without increasing prostate cancer risk —>
Should you take omega-3 pills? Or try to have two to servings of omega-3 rich fish a week, as the American Heart Association recommends? It may seem a bit murky if you follow headlines about nutrition and health. That's why researchers at the Intermountain Healthcare Heart Institute continue to research the potential benefits and risks of this popular supplement, especially when it comes to prostate cancer risk and heart health.
In one study, the Intermountain research team identified 87 patients who were part of the Intermountain INSPIRE Registry and had developed prostate cancer. These patients were also tested for plasma levels of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), which are two common omega-3 fatty acids. When compared to a matched control group of 149 men, the researchers found that higher omega-3 levels were not linked with elevated prostate cancer risk.
Viet T. Le, MPAS, PA, researcher and physician assistant at the Intermountain Healthcare Heart Institute, said they undertook this study in light of findings from a 2013 paper from the Journal of the National Cancer Institute that suggested a possible link between higher omega-3 plasma levels and the development of prostate cancer, one that has been debated since publication.
"If I'm recommending omega-3 for my patients to save their hearts, I want to make sure I'm not putting them at risk for prostate cancer," said Le. "Our study found no evidence of a link between the two." In the second study presented at the 2019 American Heart Association Scientific Sessions, the Intermountain researchers looked at 894 patients undergoing coronary angiography (a test that shows how blood flows through the arteries in the heart). These patients had no prior history of heart attack or coronary artery disease, however upon their first angiogram, about 40% of those patients had severe disease and about 10% had three-vessel disease, Le said.
Researchers also measured patients' plasma levels of omega-3 metabolites, including DHA and EPA. Those patients were then followed to see who had subsequent heart attack, stroke, heart failure, or who died. Researchers found that patients who higher rates of omega-3 metabolites had lower risk of those follow up adverse effects regardless of whether they had severe disease or not on their initial angiogram.
"This study is important because we looked at how omega-3 helps patients who have already developed disease, and its effects on survival — both in getting to the first angiography to be diagnosed (vs. having a heart attack or worse before even knowing they have heart disease) and thereafter," said Le. "While a seeming association between higher plasma omega-3 levels and the findings of severe heart disease upon initial angiogram might raise alarms that omega-3 isn't beneficial, they did live to see a doctor and get diagnosed," Le added. "And we saw a link between higher levels of omega-3 and their survival rate thereafter."
Story Source: Materials provided by Science Daily. Intermountain Medical Center. "Omega-3 shows protection against heart disease-related death, without prostate cancer risk." ScienceDaily. ScienceDaily, 17 November 2019. www.sciencedaily.com/releases/2019/11/191117165610.htm.
HIFU is an FDA approved precise and targeted therapy for prostate cancer that reduces the risk of complications caused by surgery and radiation. Focal Therapy is not associated with incontinence, and erectile dysfunction is just under 10%. Sparing of the urethra avoids scar tissue formation which, when present, may diminish the urinary stream. The eventual need for additional therapy is now under 10%.
Dr. Michael Lazar offers a HIFU Program in partnership with HIFU Prostate Services, LLC (HPS). HIFU Prostate Services, LLC (HPS) is a leading provider of minimally-invasive prostate cancer treatments using High Intensity Focused Ultrasound (HIFU). HIFU prostate treatments are available at San Francisco, Marin County, and Santa Rosa.
HIFU has many proven advantages over traditional treatment modalities for prostate disease. Call (707) 546-5553 to make an appointment with Dr. Lazar. Visit www.CaliforniaHIFU.com for more information. Fill out our online questionnaire to see if you qualify.


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At-Home Pedicure Treatments near Brentford
Looking for high-quality mobile pedicure treatments near Brentford? We've got you covered with 31 trained and vetted therapists operating nearby. Instantly book your first LeSalon experience today.
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text:
My eyes made contact with Nneka's and she knew I was looking at her ass. My eyes opened a little wider as I realized she knew. She gave me a little grin.
I apologized and smiled but then my eyes could not help but pivot down to her breasts. Her shirt was tight, and her boobs were large. Her nipples were hard and poking out at me. Between the colder air in the house and the cold air of the refrigerator, her nipples were poking out of her shirt.
"Whoops," Nneka said as she covered her breasts with her hands.
Nneka looked around the room as though she were looking for something to cover her up.
"Cold air will do that." I joked.
"Yes, it does," Nneka said nodding and still looking around.
"It's not noticeable," I told her pretending like her nipples weren't poking out at me. "Seriously, it's all good. You can't tell anything."
"I should probably put another shirt on or something," Nneka said as she was still covering her breasts.
"I shouldn't have come over unannounced," I said still trying to make her feel better. "Don't worry about it though. It happens to everyone."
"I know, it's just I don't know you that well,'' Nneka said.
"What a great way to get to know each other better," I said smiling.
"Yes, sure, the perfect way to get to know your neighbor better."
"You realize you are still holding your breasts with an egg in each hand?" I said with a smile.
"Yes, I realize that." Nneka said smiling and starting to be less nervous. "I guess I shouldn't be worrying about it. We are both adults."
"I have seen women without a bra before," I said flirting. "As beautiful as you are, I can still handle myself. I promise not to stare."
Nneka lowered her hands from her breasts. Her nipples were still very hard and poking out of her shirt. I couldn't help but stare.
"Excuse me!!" Nneka said.
My eyes left her breasts and made eye contact with Nneka.
"Uhm…what happened to not staring?" Nneka asked smiling.
"I just, uhm, it's just. Well, you have perfect breasts." I blurted out.
"What?" Nneka asked with a confused look on her face.
"They are amazingly perfect. I mean, wow". I replied.
There was a pause as Nneka looked at me. Nneka asked "you really think so?"
"Yes, I do!" I replied.
"No, they are not perfect." Nneka said as she was now looking down at her breasts.
"You can so pull off this look. You should go braless all the time." I said confidently.
"Whatever." Nneka smirked back.
"Really, you should. It's a sexy look. You are probably one of the only a few women who can pull it off. Your beasts just have that build that looks good in clothes without a bra." I stated.
"Why don't we keep this conversation about my breasts to ourselves. I really don't want my husband to know we were talking about this. Much less me standing in front of you like this." Nneka said.
"I understand. This stays with us." I replied.
"Here are your eggs," Nneka said as she handed me the eggs.
Nneka started walking towards the door and I followed.
"Thank you for the eggs!" I said as I walked out the front door.
"Thank you for the compliments!" Nneka said with a big smile as she closed the door behind me.
I rushed home and ran upstairs to my bedroom to look out the window. Thirty minutes went by and Nneka had not returned to the backyard. I waited patiently and soon she walked back out on her deck.
Nneka had on a swimsuit. It was a very skimpy swimsuit. The tops barely covered her breasts. The bottoms were such little material I had to look hard to see any off it. The back of the bottoms covered only a small portion of her ass. The front of her bottoms covered her pussy and nothing more. It was the lowest cut bikini I had ever seen. She also had on a pair of sunglasses.
Nneka walked over and got a lounge recliner and positioned it flat but facing me. She then sat down on the recliner facing in my direction. I stepped back from the window. I was worried she could see me.
She propped her head up on a towel and looked right at my window. With the sunglasses, I couldn't tell if she was looking at me or if her eyes were closed.
I waited a few moments and moved back up closer to the window. She laid there on the chair with her legs slightly spread. I was so turned on. My dick was hard. I reached down and grabbed myself. I slowly stroked my dick as I watched her. She has such an amazing body. Except for the tiny piece of material, she was wearing, she was basically naked.
I wanted to go down and talk to her again but I wasn't sure what to do. I couldn't figure out if she was out there wanting me to look at her or if she had no clue, I was watching her.
I pulled my shorts down and pulled out my dick. I stepped closer to the window. She was looking right at me. I still couldn't tell if she knew I was watching her or if her eyes were closed with those sunglasses.
As I was stroking my dick in the window, Nneka sat up. She undid her swimsuit top and took it off. I almost came watching her take off her top. Her breasts were amazing. She grabbed some lotion and started rubbing it seductively on her breasts.
Nneka was looking my direction and suddenly stopped putting lotion on and put her top back on. She then reached down and grabbed her phone.
My phone started ringing. It was Nneka. I was nervous. I thought I had been caught.
"Hello," I answered in a nervous voice.
"Hi, this is Nneka." She said calmly.
"Yes, hi. Everything ok?" I asked.
"I'm sorry to bother you, I'm sure you are in the middle of cooking your eggs, but I wanted to see if you could help me out with something?" Nneka asked.
"Sure, what do you need?" I said more confidently after realizing she wasn't calling because I got caught watching her.
"Could you come over? It will only take two minutes of your time and that's all I need." Nneka said in a flirty voice.
"Sure, I'll be right there." I said as I was pulling up my shorts.
"I'm in the backyard and the side gate is unlocked. Come in on the side of the house." Nneka explained.
"Yes, see you in a second." I said.
I ran down the stairs and out the front door. I hurried through the side gate and walked into her backyard. I slowed down when I saw her in the swimsuit.
"Hey," I said as I walked up.
"Thanks for coming over." Nneka said with a huge smile.
"No problem. How can I help?" I said.
"Ok, I was hoping you could help with putting lotion on my back. I hate to ask but I don't want to get charred and I knew you were home. I hope you don't think it's to forward of me to ask." Nneka said.
"Sure. I'd love to help. I'm glad you asked." I replied.
"I was just thinking since you already saw me earlier, maybe you would be ok with putting lotion on me???" Nneka questioned.
"No problem. Where's the bottle?" I answered.
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An investment of $1,000 in 1965 in Berkshire Hathaway stock (BRK) would have grown to $15.3 million at the end of 2016. It has averaged a 20% return annually for the past 50 years. People who buy something each month take advantage of drops in the market, even by adding $100 or so per month. Any good investment advisor will tell you that. Quality stocks plus patience will treat you well.
"One of the penalties for refusing to participate in politics is that you end up being governed by your inferiors."
How about a He-too movement for men having their lives ruined by bogus assault charges.
"Democrats don't seem to accept the legitimacy of any Republican."
Mark Steyn SteynOnline.com on Fox News 11-20-18
"Democrat Dayton mass killer supported gun control, just like ALL 2020 Democrat presidential candidates."
TheLibertyDaily.com 8-5-19
The killer was a registered Democrat and voted in two Democrat primaries. He also praised Democrat socialists Bernie Sanders, Elizabeth Warren and Satan.
Booker, Bernie and Beto were blaming Donald Trump for "stoking hate, white supremacy," etc. All Demos running are ardent Trump-haters.
"Diversity: a euphemism for discrimination against whites."
Joseph Sobran Sobran.com July 2003
Donald Trump has achieved record low unemployment and record low minority unemployment. Not bad for a first-time candidate. Why not shoot for the top.
Montgomery County, Maryland is a wealthy liberal hotbed which voted 4 to 1 for H.R. Clinton over Donald Trump. Rich areas around the USA voted Democrat in elections going back decades. Montgomery County voters are now fighting "affordable housing" in their area.
Will Grigg was right when he said "totalitarianism is defined by abundance and unintelligibility of laws."
Shoot for the top
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Southampton Village and the surrounding hamlets of Tuckahoe, Shinnecock Hills and North Sea offer proximity to bays and the ocean, please excellent shopping and dining opportunities. Here are five that could be yours this winter for a cool million.
This 1,925-square-foot Postmodern has 3 bedrooms and 3 baths. The home has new finishes and open entertaining areas. The 0.4-acre property is South of the Highway and has waterviews, a pool and a dining and sunning area.
In the North Sea hamlet, live on Fish Cove in this 1,164-square-foot Raised Ranch. The 5-bedroom, 2-bath house sits on 0.41 acres. The open kitchen/dining room has new granite counter tops, a large deck, a living room, a sun room, a second kitchen, a pergola and a garage. Use a private dock and access North Sea Harbor and Peconic Bay.
This 2-story Traditional just west of Southampton Village sits on .67 acres. There are 6 bedrooms and 3 baths, a light-filled cathedral ceiling-ed great room with fireplace, and a gourmet kitchen. French doors open to a large deck and private back yard with heated pool.
This 2,500-square-foot Colonial on .57 acres has 4 bedrooms and 2.5 baths. The property is just outside Southampton Village and minutes to Main Street and the ocean. Amenities include a heated pool.
This 2,000-square-foot, 2-story Contemporary on .60 acres has 4 bedrooms and 3.5 baths. The living room has high ceilings and additional rooms include a kitchen and dining area. There is a pool and deck on the property, which is near Southampton Village, and there is community access to tennis.


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Light-emitting diodes (LED) are quickly becoming more efficient than the familiar incandescent light bulb or florescent tube. NFPA's Fred Durso had the chance to interview John Bullough, of the Rensselaer Polytechnic Institute Lighting Research Center, on his upcoming presentation at SUPDET 2013.
Bullough has been looking into LEDs as emergency signaling lighting. Specifically, he's been experimenting with the intensity of the light and the duration of the light bursts, and how those impact their effectiveness. To find out how LEDs can be applied in both emergency safety and everyday operations, watch the full interview below.


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We have a few extra copies of our yearbooks available for cash/cheque sale in the Bellevue office. 2015-2016 is $20 and 2016-2017 is $25.
Archives > December 2017
December 13, 2017
Message for Bellevue Families RE: ECVS School Startup Schedule
École Champs Vallée School startup schedule released. Black Gold Regional Division No. 18 and École Champs Vallée School are excited to announce that the startup schedule (see attached) for the new school has been released at December's Regular Board Meeting. Opening day with students and staff has been scheduled for February 20, 2018, right after… Read more »
December 10, 2017
Hot Lunches – Cycle 2 – Open for orders until Dec. 18
December 05, 2017
December School Newsletter Now Available
December Newsletter


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The Natives Were Friendly So We Stayed the Night(1977)
A non fiction book by Noel Barber
Noel Barber became known as Foreign Correspondent for the "Daily Mail". He was the first Briton to reach the South Pole after Scott, he was stabbed five times covering the wars in Morocco and shot in the head during the Hungarian uprising. After writing a number of works of non-fiction, he started to write fiction in his seventies, and became a best-seller with such books as "Tanamera", "A Farewell to France", "A Woman of Cairo" and "The Other Side of Paradise".
Used availability for Noel Barber's The Natives Were Friendly So We Stayed the Night
Hardback Editions
February 1979 : UK Hardback
December 1977 : UK Hardback
September 1977 : UK Hardback
Paperback Editions
June 1989 : UK Paperback


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Dear Players,
To make this special weekend even better, we are holding a 20% off sale on all Character Cards! You can grab yourself a discounted Character Card starting today until 10AM Pacific on July 23rd. After that, the cards will be going down to 10% off and back to normal on July 25th. Hurry now to take part in this awesome sale!
Thank you,
-Mabinogi Team-
Thank you, Mabinogians, for your continued support. To show our appreciation we're having a Double Rainbow this weekend! You'll get twice the experience, twice the AP, and twice the items for defeating monsters and enemies in Erinn. Be sure to join us from Midnight July 20th to Midnight July 23rd, 2012 and get yourself a nice boost for your characters!
Enjoy your Fantasy Life!


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This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.
Check back here for the latest event updates, our Amish horse & buggy ride schedule, Strawberry Festival dates and more.
Click or tap on an event for more details.
Events for June 14, 2019
Events Search and Views Navigation
9:00 am
Amish Quilter
Rachel Esh is new addition to our farm, she has a craft shop on our 15-acre farm. Rachel handcrafts Amish dolls and little souvenirs that fit perfectly into a suitcase. Rachel greats each guest that visits her shop and even demonstrates how she creates her handmade items. If you're looking for an authentic handmade Amish […]Find out more »
Chris Lubkemann is the "Resident Woodcarver" at The Amish Farm and House. While you're here, stop by the woodshop to meet Chris and to watch him work. You can purchase wood carvings and gifts that Chris has made in our gift shop. Chris's woodshop is open Monday-Saturday from April through October during our normal business […]Find out more »
Amish Made Chicken BBQ
You can't leave the farm without a meal our new Amish Chicken BBQ Barn! David, his wife Liz, and their five children will be barbequing delicious chicken and rib dinners. They have several delicious lunch and dinner options. Enjoy your meal or snack right here on our 15-acre farm. Amish Made Chicken BBQ Entrées: Chicken […]Find out more »
Blacksmith-Andrew Reist
The Amish Farm and House is pleased to host members of the Pennsylvania Artist Blacksmith Association for special events. Our Civil-War era blacksmith shop comes alive as the blacksmith pounds away on the anvil. Our resident blacksmith, Andrew Reist, will demonstrate the art of blacksmithing and explain the importance of blacksmithing both in colonial America […]Find out more »
Amish School Teacher
During your farm visit, don't forget to visit our Amish 0ne-room schoolhouse! Our schoolhouse was built by Amish and is the only modern Amish school open to the public. This summer visit with Rose, our schoolhouse teacher. Rose loves being able to chat with curious people from all over the world. Rose being part of […]Find out more »
11:00 am
Buggy Rides
Buggy Rides will only be held under good weather conditions. Information About Our Horse & Buggy Rides: How much does it cost? Horse and buggy rides are $6 per person. Cash only, please. Where does the ride go? You will clip clop along paths on our 15-acre farm. Part of the ride will take you […]Find out more »


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Hub overview Hub is a command-line tool that wraps git and provides extra functionality that makes working with GitHub easier.
Sometimes we start writing code without managing our branches in advance. Then we make commits in master (or some other base branch) when we intended to carve off a new feature branch.
Publishing software packages is already pretty easy, so what does GitHub's Package Registry offer that we don't already have?
Create GitHub personal access tokens for the command line
Nothing is certain, except death and taxes and merge conflicts. -Benjamin Franklin
Cleaning up unused tags is an important part of Git housekeeping. This guide will show you how to delete tags from both local and remote Git repositories.
Git is an open-source version control system (VCS). In order to use Git to track changes in your code from the command line, you'll need to download, install and configure it on your computer.
Tab completion, or auto-completion, is essential if you're using Git on the command line. Tab completion is a nice feature of many shells that allows you to complete a word by hitting tab.
I've wanted to start blogging again after a few years off. I was thrilled to find that I can blog using markdown in Vim and publish using git.
When you're using git routinely, it's helpful to know which branch you're currently on without having to type git status or git branch.
Finding guides


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Location & Currency
Puig Touring Wind Screen for Triumph Tiger 800 (2011+)
For long distance rides, PUIG introduces the Touring series to minimize the windblast against the rider. These screens raise the windblast in several centimeters allowing the rider to keep a more comfortable position riding the motorcycle.
Manufactured with acrylic of high impact of 3mm, resistant and durable.
Note: due to the size of the box, international orders may be shipped USPS depending on actual shipping cost in order to save you additional shipping costs
Puig Wind Screens Part #Black (5652N)Dark Smoke (5652F)Light Smoke (5652H)Clear (5652W)
*contact us for other custom color options
Fits:Triumph Tiger 800/800XC (2011+)
© 2004 - 2020 Motovation Accessories. All rights reserved.


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You Need To Hear This Slam Poem
If you've never heard of the Women of the World Poetry Slam competition held each year, you are missing out. For proof, look no further than the slam poem "Black Feminist" by Jillian Christmas, which was performed at last year's competition but is rightly getting a lot of attention online now. The poem, delivered in hushed, precise tones, calls out White Feminism and the ways in which white feminists are not inclusive of black women. And it's something all white women who identify as feminists should hear.
Mainstream feminism in the United States has a sad history of being focused primarily (and at times exclusively) on the interests of straight, white, middle class women. And even today, there's a distinct lack of intersectional feminism, a concept pioneered by black academic Kimberlé Crenshaw. In a nutshell, intersectional feminism maintains that various forms of oppression, such as sexism, racism, classism, etc., are interconnected and that you can't separate out a person's various identities and try to address the injustices they face as a result as though they are were wholly separate issues.
Which sounds self-evident, but in practice often goes unacknowledged in feminist circles.
For a long time, feminism has used straight, white, cisgender, middle-class, and otherwise privileged women as its default, but that has started to change more and more in recent years, thanks in large part to women of color (as well as women from other marginalized groups) speaking out about the problem. "Black Feminist" by Jillian Christmas highlights the issues with the way black women are often treated in feminist spaces, and it's a must-listen for feminists everywhere.


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Rexcell is a wholly owned subsidiary of Duni AB. We have one of the most advanced paper mills in Europe for the production of specialised tissue. This is located in Skåpafors, Dalsland, Sweden.
Our history begins in 1898 when the first paper machine started in Skåpafors. This due to a move of the paper manufacturing from the paper mill in close by village Gustavsfors. Since then we have consistently developed innovative products and processes. For instance, we produced the world's first coloured napkin, and were first in Europe with commercial airlaid technology.
"Our mission is to create value for our customers by delivering superior competitive materials based on tissue and airlaid technology."
Lars Andersson, Plant & Production Manager


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New Hanover County health leaders are asking local residents to improve the health of our community by participating in the 2015 New Hanover County Health Survey.
Conducted every three – four years, the New Hanover County Health Survey is part of a larger health planning process to identify the health status, disparities, gaps and unmet needs of the community in balance with community resources, strengths and perceptions. Beginning in June and continuing through the summer, the New Hanover County Health Department, in collaboration with UNCW College of Health & Human Services, will be surveying more than 3,500 adult County residents.
The results of the survey will be used to:
- Better understand the respond to current and emerging health needs in the community
- Develop new policies
- Improve existing health programs and services; and
- Plan prioritize and target resources
The online survey and additional information is available online at www.surveyNHC.com. Paper copies are also available at all New Hanover County Library branches. The survey takes approximately 15 minutes to complete and it is completely confidential and anonymous.
By answering the survey, you will have done your part to improve health for everyone in our county. Please remember to share this information with your family and friends.


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Balloons of Stafford was developed from a desire to create unique, stylish balloons. We specialise in balloon decor; from small local functions to large scale events. Our ethos is simple; to offer great service and memorable products that you'll be delighted with.
We supply balloons in and around the Staffordshire area and are the recommended balloon suppliers for many beautiful venues in the county.
Choose from our product selection below for more information on our most popular balloons or browse our gallery and Pinterest board for more ideas and inspiration.


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Business Insider (@businessinsider)
Each thing that you might want to know to start out your personal enterprise. Nonetheless, only a few schools or universities provide formal programs in management consulting. As a result of small businesses battle to make use of and perceive digital advertising, it's no shock that lower than half of respondents discover their advertising efforts effective. fifty seven p.c of small business homeowners surveyed have been over the age of fifty, a small enhance 12 months over 12 months.
The projections are made by combining forecasts from autoregressive built-in transferring average (ARIMA) and exponential smoothing with damped development (ESWDT) fashions, with some changes made to take account of research undertaken by the Department of Employment, Expertise, Small and Family Business and identified future business developments.
Whereas each community has its own native analytics, no social media supervisor wants to spend time every week, month or yr gathering knowledge and hand-inputting it into a spreadsheet. Bil Gaines, the digital advertising and marketing director of Custom Creatives says that very few small businesses make use of cross-channel advertising. And most small business homeowners oversee so many facets of their corporations—from gross sales to finance to human sources to each day operations—that advertising unintentionally falls down the checklist of priorities.
Promoting Skilled is a digital market and on-line promoting finest multi vendor wordpress theme 2016 3a WordPress theme with 7 demos.Posted on Might 19 2016 by Marisa Tracie in Weblog Enterprise Enchancment WordPress Right now we dwell social media promoting in social …


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The Northwest Ohio Human Resource Association (NOHRA) is a not-for-profit organization dedicated to serving and advancing the human resource profession. NOHRA is a local affiliate of the Society for Human Resource Management (SHRM). We are a dynamic, growing chapter that has received SHRM's Superior Merit Award for outstanding chapter achievement. We are governed by a constitution that is available for your review.
NOHRA - 2020 Pre-paid option
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Mark your calendar for the inaugural webinar in the NOHRA Workforce Readiness Lunch & Learn Webinar Series with Jim...
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How to add some pictures in the homepage ?
Hi i'm able to install, see different categories in the home page.
Now how can i add some pictures in the homepage ?
If i need to change the code, what file will that be, i do have some node.js experience.
Thanks !
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Michelle Obama Hilariously Breaks Down Why Melania Trump's Inauguration Gift Exchange Appeared So Awkward
The former FLOTUS also explained to Ellen Degeneres how Barack stepped in and saved the day.
It's a good thing Tracy Morgan has gotten used to controversy because it keeps coming his way. Now that his gay bashing rant has become old news, Tracy has alienated yet another group: New Jerseyans. It stems from the comedian's belief that the state is "Third World."
The New York Post says Tracy was taped in a heated exchange on the roof of the Silver Towers on West 42nd Street after he crashed a barbeque. He was apparently arguing that "the world is a ghetto." He then went to another party and went into a rant after party guest Konstantin Burshteyn quipped that they were lucky to be at a private party overlooking the Hudson.
In response Morgan said, "I don't give a [bleep] what you think . . . This is my mother[bleeping] generalization, not yours." He went on, "New Jersey, right across the river, is the Third World." Burshteyn refuted such claims, but Morgan continued, "Believe me, dude—I live in a very affluent neighborhood right now and my house, one of them is $2 million, and there is some ghetto [bleep] going on there." However, earlier in the evening Morgan did note, "I'm from the ghetto, and that ain't bad.... I will never be disconnected from my roots. You disconnect the tree from the roots and what happens to the tree? It [bleep]ing dies."
(Photo: Brad Barket/PictureGroup)
The former FLOTUS also explained to Ellen Degeneres how Barack stepped in and saved the day.
"When my teacher asks me a question thinking I'm not paying attention, but I get it right."