Triple

T15645508
Position Surface form Disambiguated ID Type / Status
Subject Zhonghe–Xinlu line E376165 entity
Predicate hasStation P35 FINISHED
Object Huilong station 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: Huilong station | Statement: [Zhonghe–Xinlu line, hasStation, Huilong station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huilong station
Context triple: [Zhonghe–Xinlu line, hasStation, Huilong station]
  • A. Huilong station chosen
    Huilong station is a metro station in New Taipei, Taiwan, serving as a key terminal stop on the Taipei Metro network.
  • B. Huoying station
    Huoying station is an interchange stop on the Beijing Subway that connects passengers to Line 13 and other transit services in the northern part of the city.
  • C. Luyuan station
    Luyuan station is a subway station on Beijing's Line 8 serving passengers in the city's urban transit network.
  • D. Liyuan Station
    Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
  • E. Tiantongyuan station
    Tiantongyuan station is a subway station in Beijing, China, serving the northern residential area of Tiantongyuan on the city's metro network.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed5b8b081908d7127964eed3b09 completed April 16, 2026, 2:52 a.m.
Created at: April 10, 2026, 4:15 a.m.