Triple

T15494330
Position Surface form Disambiguated ID Type / Status
Subject Anyang Museum E378774 entity
Predicate operatedBy P86 FINISHED
Object Anyang city government E241609 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: Anyang city government | Statement: [Anyang Museum, operatedBy, Anyang city government]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anyang city government
Context triple: [Anyang Museum, operatedBy, Anyang city government]
  • A. Anyang
    Anyang is an ancient city in northern China renowned as one of the historical capitals of the Shang dynasty and a major archaeological site.
  • B. Anyang chosen
    Anyang is a mid-sized South Korean city in the Seoul Capital Area known for its residential districts, light industry, and proximity to central Seoul.
  • C. Yao City government
    Yao City government is the municipal administrative body responsible for local governance, public services, and policy implementation in Yao, Japan.
  • D. Yangju City Government
    Yangju City Government is the municipal administrative authority responsible for local governance, public services, and policy implementation in Yangju, South Korea.
  • E. Asan City Government
    Asan City Government is the municipal administrative authority responsible for local governance, public services, and policy implementation in the city of Asan, South Korea.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fad723481908d2aa33e8f065f2f completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3662f3388190b75ffe3ce418f36d completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:49 a.m.