Triple

T735485
Position Surface form Disambiguated ID Type / Status
Subject Chan E14920 entity
Predicate romanizesChineseCharacter P2508 FINISHED
Object E87685 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: 陈 | Statement: [Chan, romanizesChineseCharacter, 陈]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 陈
Context triple: [Chan, romanizesChineseCharacter, 陈]
  • A. chosen
    陳 is a common Chinese surname and character with historical roots, widely used across Chinese-speaking communities and often romanized as "Chan," "Chen," or similar variants.
  • B.
    苏 is the standard Chinese abbreviation used to refer to Jiangsu Province in eastern China.
  • C.
    詹 is a Chinese surname and character commonly romanized as "Chan" in Cantonese.
  • D. Chen Cheng
    Chen Cheng was a prominent Chinese military leader and politician who played key roles in the Nationalist government and later served as Premier and Vice President of the Republic of China in Taiwan.
  • E. Ding Ruchang
    Ding Ruchang was a late Qing dynasty Chinese naval officer best known for leading the Beiyang Fleet during the First Sino-Japanese War.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aa9ba3888190889a1ad554f73c5e completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69a654e1d10c8190b69b30cc70add604 completed March 3, 2026, 3:26 a.m.
Created at: March 1, 2026, 7:37 p.m.