Triple

T8705145
Position Surface form Disambiguated ID Type / Status
Subject Xiaogan Municipal People's Government E206629 entity
Predicate governs P760 FINISHED
Object Xiaonan District E263374 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: Xiaonan District | Statement: [Xiaogan Municipal People's Government, governs, Xiaonan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xiaonan District
Context triple: [Xiaogan Municipal People's Government, governs, Xiaonan District]
  • A. Xiaonan District chosen
    Xiaonan District is the central urban district and administrative seat of Xiaogan City in Hubei Province, China.
  • B. Xiaoting District
    Xiaoting District is an urban administrative district of Yichang in Hubei Province, China, known for its location along the Yangtze River and its role in the region’s industrial and transportation network.
  • C. Yuhua District
    Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • D. Jinyuan District
    Jinyuan District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
  • E. Shuangxi District
    Shuangxi District is a rural, mountainous district in eastern New Taipei City, Taiwan, known for its rivers, old streets, and natural scenery.
  • 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_69ca835645e881908f00e3c8b51da81d completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58fb43f081909df5d1e31cb1ec04 completed March 31, 2026, 11:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d09b22da4c81909aacc9c4a6af379c completed April 4, 2026, 5:01 a.m.
Created at: March 30, 2026, 6:34 p.m.