Triple

T7767899
Position Surface form Disambiguated ID Type / Status
Subject Huaihua E178994 entity
Predicate hasUrbanDistrict P11388 FINISHED
Object Hecheng District E691967 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: Hecheng District | Statement: [Huaihua, hasUrbanDistrict, Hecheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hecheng District
Context triple: [Huaihua, hasUrbanDistrict, Hecheng District]
  • A. Hecheng District chosen
    Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
  • B. Xialu District
    Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
  • C. Zhengxiang District
    Zhengxiang District is an urban administrative district of Hengyang City in Hunan Province, China, known for its role as one of the city's central built-up areas.
  • D. Yuhua District
    Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • E. Sanzhi District
    Sanzhi District is a rural coastal district in northern Taiwan known for its scenic landscapes, hot springs, and agricultural produce within New Taipei City.
  • 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c70435b7f88190a5e68e6ae701c58f completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9cd7f9b2c81908a1f77a9cc37a0be completed March 30, 2026, 1:10 a.m.
Created at: March 27, 2026, 4:11 p.m.