Triple

T4090182
Position Surface form Disambiguated ID Type / Status
Subject E87686 entity
Predicate CantoneseRomanization P51400 FINISHED
Object Chan E14920 NE FINISHED

How this triple was built (3 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: Chan | Statement: [詹, CantoneseRomanization, Chan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chan
Context triple: [詹, CantoneseRomanization, Chan]
  • A. Chan chosen
    Chan is a common Chinese surname shared by many notable individuals across various fields worldwide.
  • B. Chen
    Chen is a common Chinese surname borne by many notable individuals across politics, arts, science, and technology.
  • C. Chang
    Chang is a 1927 silent documentary-style adventure film set in the jungles of Siam, co-directed by Merian C. Cooper and Ernest B. Schoedsack, known for its depiction of human–nature conflict and elephant stampedes.
  • D. Chun
    Chun is the given name of Peng Chun Chang, a prominent Chinese philosopher and diplomat who helped draft the Universal Declaration of Human Rights.
  • E. Kwan
    Kwan is a Chinese-origin surname shared by many individuals, including the renowned American figure skater Michelle Kwan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: CantoneseRomanization
Context triple: [詹, CantoneseRomanization, Chan]
  • A. cantoneseYaleForm chosen
    Indicates the written form of a term using the Yale romanization system for Cantonese pronunciation.
  • B. ChinesePinyin
    Indicates that one entity is the Chinese pinyin (romanized phonetic transcription) representation of another entity.
  • C. WadeGilesForm
    Indicates that one entity is the Wade–Giles romanized form corresponding to another entity’s written or spoken Chinese form.
  • D. ChineseNameTraditional
    Indicates that an entity’s name is given in traditional Chinese characters.
  • E. hasRomanizationOf
    Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
  • F. None of above.

Provenance (4 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_69aed94425148190be337845d56fac22 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefcab0a1c8190a1b0ca48ebc95b31 completed March 9, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5769e8b188190a6356c325d0551ea completed March 14, 2026, 2:54 p.m.
PD Predicate disambiguation batch_69aef909c9c88190b09d48dad325a83c completed March 9, 2026, 4:44 p.m.
Created at: March 9, 2026, 3:39 p.m.