class_docstr: A deterministic Intent parser implementation based on a dictionary
  
  This intent parser is very strict by nature, and tends to have a very good
  precision but a low recall. For this reason, it is interesting to use it
  first before potentially falling back to another parser.
class_docstr_tok: ["A","deterministic","Intent","parser","implementation","based","on","a","dictionary","This","intent","parser","is","very","strict","by","nature",",","and","tends","to","have","a","very","good","precision","but","a","low","recall",".","For","this","reason",",","it","is","interesting","to","use","it","first","before","potentially","falling","back","to","another","parser","."]
docstr: Loads a :class:`LookupIntentParser` instance from a path
  
  The data at the given path must have been generated using
  :func:`~LookupIntentParser.persist`
docstr_tok: ["Loads","a",":","class",":","`","LookupIntentParser","`","instance","from","a","path","The","data","at","the","given","path","must","have","been","generated","using",":","func",":","`","~LookupIntentParser.persist","`"]
code: def from_path(cls, path, **shared):
      """Loads a :class:`LookupIntentParser` instance from a path
  
      The data at the given path must have been generated using
      :func:`~LookupIntentParser.persist`
      """
      path = Path(path)
      model_path = path / "intent_parser.json"
      if not model_path.exists():
          raise LoadingError(
              "Missing lookup intent parser metadata file: %s"
              % model_path.name
          )
  
      with model_path.open(encoding="utf8") as pfile:
          metadata = json.load(pfile)
      return cls.from_dict(metadata, **shared)
  
imports: from __future__ import unicode_literals
  import json
  import logging
  from builtins import str
  from collections import defaultdict
  from itertools import combinations
  from pathlib import Path
  from future.utils import iteritems, itervalues
  from snips_nlu_utils import normalize, hash_str
  from snips_nlu.common.log_utils import log_elapsed_time, log_result
  from snips_nlu.common.utils import check_persisted_path, deduplicate_overlapping_entities, fitted_required, json_string
  from snips_nlu.constants import DATA, END, ENTITIES, ENTITY, ENTITY_KIND, INTENTS, LANGUAGE, RES_INTENT, RES_INTENT_NAME, RES_MATCH_RANGE, RES_SLOTS, SLOT_NAME, START, TEXT, UTTERANCES, RES_PROBA
  from snips_nlu.dataset import validate_and_format_dataset, extract_intent_entities
  from snips_nlu.dataset.utils import get_stop_words_whitelist
  from snips_nlu.entity_parser.builtin_entity_parser import is_builtin_entity
  from snips_nlu.exceptions import IntentNotFoundError, LoadingError
  from snips_nlu.intent_parser.intent_parser import IntentParser
  from snips_nlu.pipeline.configs import LookupIntentParserConfig
  from snips_nlu.preprocessing import tokenize_light
  from snips_nlu.resources import get_stop_words
  from snips_nlu.result import empty_result, intent_classification_result, parsing_result, unresolved_slot, extraction_result
label_desc: Use image node_id 20 for calling the LookupIntentParser obj's underlying member method code with example usage: obj.from_path(cls, path) and returns: cls