Triple

T16386186
Position Surface form Disambiguated ID Type / Status
Subject Taipei Metro Wenhu line E397927 entity
Predicate serves P98 FINISHED
Object Neihu District NE NERFINISHED

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: Neihu District | Statement: [Taipei Metro Wenhu line, serves, Neihu District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neihu District
Context triple: [Taipei Metro Wenhu line, serves, Neihu District]
  • A. Neihu District chosen
    Neihu District is a suburban and technology-focused district in northeastern Taipei, Taiwan, known for its science parks, residential communities, and natural scenery.
  • B. Huichuan District
    Huichuan District is an urban administrative district within the prefecture-level city of Zunyi in Guizhou Province, China.
  • C. Xialu District
    Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
  • D. Linwei District
    Linwei District is an urban administrative district in Weinan, Shaanxi Province, China, serving as the city's central political and economic area.
  • E. Yunhe District
    Yunhe District is an urban administrative district that serves as the central area and governmental seat of Cangzhou in Hebei Province, China.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e3263d260081909db9ac6016d5738a completed April 18, 2026, 6:35 a.m.
Created at: April 10, 2026, 5:08 a.m.