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name: parsing-and-normalization description: "Parse and normalize Chinese time, money, location, and related entity strings." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

Parsing and normalization

Use this sub-skill when a string should be interpreted as a structured Chinese entity rather than just cleaned.

Include here

• Time parsing and extraction: parse_time, jio.ner.extract_time
• Money parsing and extraction: parse_money, jio.ner.extract_money, money_num2char
• Location parsing and recognition: parse_location, recognize_location
• Phone attribution: phone_location, cell_phone_location, landline_phone_location
• Identity and plate parsing: parse_id_card, extract_id_card, parse_motor_vehicle_licence_plate, extract_motor_vehicle_licence_plate
• Character and idiom helpers: pinyin, char_radical, idiom_solitaire, lunar2solar, solar2lunar
• String-level parsers that depend on dictionary-backed semantics

Exclude or route elsewhere

• Raw cleanup, replacement, or HTML stripping → text-cleaning-and-extraction
• Augmentation → text-augmentation
• BIO/BIOES conversion, lexicon NER, or dataset batching → annotation-and-dataset-tools
• Dictionary loaders and higher-level analytics → dictionaries-and-language-analysis

What to read

• references/api-reference.md for signatures, return shapes, and edge notes.
• references/troubleshooting.md for noisy input, boundary, and ambiguity issues.
• scripts/smoke_parsers.py for a representative CPU-only smoke run.

Typical flow

1. Remove obvious noise first if the input is a sentence, paragraph, or clause.
2. Choose the parser that matches the target structure.
3. Read the parsed result before chaining to other helpers.
4. Keep the parser-specific options visible when the input is ambiguous.

Quick cues

• Ask for this sub-skill when the user says "parse this time string", "normalize this amount", "find the province/city", "get the pinyin", "convert lunar to solar", or "what is this car plate or ID card".
• Stay here if the task is semantic interpretation, not surface cleanup.