Triple

T6445220
Position Surface form Disambiguated ID Type / Status
Subject Wuhan Metro Line 7 E138324 entity
Predicate connectsDistrict P2564 FINISHED
Object Qingshan District E136088 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: Qingshan District | Statement: [Wuhan Metro Line 7, connectsDistrict, Qingshan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Qingshan District
Context triple: [Wuhan Metro Line 7, connectsDistrict, Qingshan District]
  • A. Qingshan District chosen
    Qingshan District is an urban district of Wuhan in Hubei Province, China, known for its heavy industry and riverside location along the Yangtze River.
  • B. Xiaonan District
    Xiaonan District is the central urban district and administrative seat of Xiaogan City in Hubei Province, China.
  • C. Jinyuan District
    Jinyuan District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
  • D. Wanhua District
    Wanhua District is one of Taipei’s oldest urban areas, known for its historic temples, traditional markets, and the popular shopping and entertainment area of Ximending.
  • E. Yuhua District
    Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central 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_69c008aa61ac8190bc96715ed79fe2d8 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0698d866c81909ef3e0a53833ff7d completed March 22, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b89caf148190a2959698e5849e12 completed March 28, 2026, 11:16 a.m.
Created at: March 22, 2026, 4:46 p.m.