Triple

T14124347
Position Surface form Disambiguated ID Type / Status
Subject Xinzhou E339987 entity
Predicate governs P760 FINISHED
Object Xinfu District E1153938 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: Xinfu District | Statement: [Xinzhou, governs, Xinfu District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xinfu District
Context triple: [Xinzhou, governs, Xinfu District]
  • A. Xinfu District chosen
    Xinfu District is an urban administrative district that serves as the central area and seat of government for Xinzhou in Shanxi Province, China.
  • B. Tiefeng District
    Tiefeng District is an urban district of the city of Qiqihar in Heilongjiang Province, northeastern China.
  • C. Yushui District
    Yushui District is the central urban district and administrative seat of Xinyu, a prefecture-level city in Jiangxi Province, China.
  • D. Xicheng District
    Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
  • E. Zhifu District
    Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6096976481909dc79066c5165a50 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a5c72008190a3c4df20480850c9 completed May 9, 2026, 11:28 a.m.
Created at: April 9, 2026, 10:22 p.m.