Triple

T4576528
Position Surface form Disambiguated ID Type / Status
Subject .台湾 E123151 entity
Predicate script P505 FINISHED
Object Han E428478 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Han | Statement: [.台湾, script, Han]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Han
Context triple: [.台湾, script, Han]
  • A. Han
    Han is a common transliteration of the historical Central Asian title "Khan," often associated with rulers and nobility in various Turkic and Mongolic cultures.
  • B. Han chosen
    Han refers to the majority ethnic group in China, historically associated with Chinese civilization, language, and culture.
  • C. Hal
    Hal is a masculine given name, commonly used as a diminutive form of Harold.
  • D. HAN
    HAN is the standard abbreviation used for the Hanshin Tigers, a professional baseball team in Japan's Nippon Professional Baseball league.
  • E. HAN
    HAN is the IATA airport code for Noi Bai International Airport, the main international gateway serving Hanoi, Vietnam.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69bd46466c7081909d07f36be2d08804 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd58dfe3508190b21836079e951a3c completed March 20, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3e656a08190bb48d2ecae1eb798 completed March 20, 2026, 11:10 p.m.
Created at: March 20, 2026, 1:10 p.m.