Triple

T6499221
Position Surface form Disambiguated ID Type / Status
Subject Langfang E148838 entity
Predicate capital P234 FINISHED
Object Guangyang District E453315 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: Guangyang District | Statement: [Langfang, capital, Guangyang District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guangyang District
Context triple: [Langfang, capital, Guangyang District]
  • A. Guangyang District chosen
    Guangyang District is an urban district of Langfang City in Hebei Province, China, located in the Beijing–Tianjin corridor and known for its role in regional transportation and commerce.
  • B. Yingquan District
    Yingquan District is an urban administrative district of the city of Fuyang in Anhui Province, China.
  • C. Yongnian District
    Yongnian District is an administrative district under the jurisdiction of Handan City in Hebei Province, China, known for its historical and cultural significance.
  • D. Tieshan District
    Tieshan District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China, known for its industrial and mining activities.
  • E. Fengrun District
    Fengrun District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei 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_69c687e9ad288190bae5bcac9c8ac855 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c68ad1c46c819089db43e7c3a8d160 completed March 27, 2026, 1:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cbabb8848190bb541957176b0ca1 completed March 28, 2026, 12:38 p.m.
Created at: March 27, 2026, 1:41 p.m.