Triple

T3942366
Position Surface form Disambiguated ID Type / Status
Subject Lu’an E92062 entity
Predicate governs P760 FINISHED
Object Jin’an District E456885 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: Jin’an District | Statement: [Lu’an, governs, Jin’an District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jin’an District
Context triple: [Lu’an, governs, Jin’an District]
  • A. Jin’an District chosen
    Jin’an District is an urban administrative district within the prefecture-level city of Lu’an in Anhui Province, China.
  • B. Jiang'an District
    Jiang'an District is an urban district of Wuhan in Hubei Province, China, known for its central location and role as a key commercial and residential area of the city.
  • C. Futian District
    Futian District is a central urban district of Shenzhen, China, known as a major commercial, administrative, and financial hub that hosts the city government and the Shenzhen Central Business District.
  • D. Tianning District
    Tianning District is an urban administrative district of Changzhou in Jiangsu Province, China, known for its historic temples and commercial centers.
  • E. Jianye District
    Jianye District is an urban district of Nanjing, China, known for its historical significance and major memorial sites related to the Nanjing Massacre.
  • 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_69aed965502c8190904ebad1203a4ae8 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedff736c8190b22e03d94c40f61a completed March 9, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69be031d16a08190b84524b7153f7f85 completed March 21, 2026, 2:31 a.m.
Created at: March 9, 2026, 3:24 p.m.