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name: rules-and-trie description: "Guides HanLP deterministic rules, sentence and string utilities, Trie/TrieDict matching, and model-backed custom dictionary overlays." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Rules And Trie

Use this sub-skill when a task mentions deterministic sentence splitting, hanlp.utils.rules, possible_tokenization, Trie, TrieDict, TupleTrieDict, custom dictionaries, dict_force, dict_combine, dict_tags, gazetteers, or longest-prefix matching.

Read First

• Read references/trie-reference.md for verified trie and dictionary APIs.
• Read references/custom-dictionaries.md for model-backed tokenizer/POS/NER dictionary overlays.
• Read references/troubleshooting.md for matching surprises, tuple keys, whitespace, and model-download boundaries.
• Run scripts/rules_smoke.py for no-download rules/string utility checks.
• Run scripts/trie_smoke.py for no-download trie and dictionary checks.

Minimal Trie Use

from hanlp_trie import Trie, TrieDict
trie = Trie({'商品': 'goods', '和服': 'kimono'})
print(trie.parse('商品和服'))
print(trie.parse_longest('商品和服'))
custom = TrieDict({'重要': 'important'})
print(custom.tokenize('第一个词语很重要'))

Trie and rule utilities can be verified without model downloads. Model-backed dictionary overlays such as tok.dict_force, tok.dict_combine, pos.dict_tags, and ner.dict_whitelist require a loaded pretrained component before they can change model output.