Triple

T777253
Position Surface form Disambiguated ID Type / Status
Subject Mao Anqing E16414 entity
Predicate givenName P17 FINISHED
Object Anqing E152399 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: Anqing | Statement: [Mao Anqing, givenName, Anqing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anqing
Context triple: [Mao Anqing, givenName, Anqing]
  • A. Anqing chosen
    Anqing is a prefecture-level city in southwestern Anhui Province, China, known historically as a regional political and military center along the Yangtze River.
  • B. Hefei
    Hefei is the capital and largest city of Anhui Province in eastern China, known as a major industrial, scientific, and educational center.
  • C. Chizhou
    Chizhou is a prefecture-level city in southeastern China known for its proximity to the scenic Mount Jiuhua, one of the four sacred mountains of Chinese Buddhism.
  • D. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • E. Wuhu
    Wuhu is a major industrial and transportation hub city in southeastern Anhui Province, eastern China, situated on the lower reaches of the Yangtze River.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a74da7648190adfad56717d564df completed March 1, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad15866b448190b20334eddca756eb completed March 8, 2026, 6:21 a.m.
Created at: March 1, 2026, 7:37 p.m.