Triple

T8636587
Position Surface form Disambiguated ID Type / Status
Subject Jingmen Municipal People's Government E204538 entity
Predicate governs P760 FINISHED
Object Jingmen city E40390 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: Jingmen city | Statement: [Jingmen Municipal People's Government, governs, Jingmen city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jingmen city
Context triple: [Jingmen Municipal People's Government, governs, Jingmen city]
  • A. Jingmen chosen
    Jingmen is a prefecture-level city in central China known for its role as a regional industrial and transportation hub within Hubei Province.
  • B. Guangshui
    Guangshui is a county-level city in central China's Hubei province, known for its historical sites and role as a regional transportation hub.
  • C. Suizhou
    Suizhou is a county-level city in northern Hubei Province, China, known for its historical sites and role as a regional transport and economic hub.
  • D. Ezhou
    Ezhou is a prefecture-level city in eastern Hubei Province, China, known for its location along the Yangtze River and its growing role as a regional transportation and industrial hub.
  • E. Zaoyang City
    Zaoyang City is a county-level city in Hubei Province, China, known for its historical significance and agricultural production.
  • 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_69ca834b903c8190add96cc651e1a477 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4760fa448190862c886bc5a6ec10 completed March 31, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d02f4d26ec8190baacf68b7e6ca0eb completed April 3, 2026, 9:21 p.m.
Created at: March 30, 2026, 6:27 p.m.