Triple

T15645494
Position Surface form Disambiguated ID Type / Status
Subject Zhonghe–Xinlu line E376165 entity
Predicate hasStation P35 FINISHED
Object Dongmen station E1231683 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: Dongmen station | Statement: [Zhonghe–Xinlu line, hasStation, Dongmen station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dongmen station
Context triple: [Zhonghe–Xinlu line, hasStation, Dongmen station]
  • A. Dongmen Station chosen
    Dongmen Station is a key Taipei Metro interchange hub connecting multiple subway lines in central Taipei, Taiwan.
  • B. Dongsi station
    Dongsi station is a Beijing Subway interchange station in central Beijing that serves both Line 5 and Line 6.
  • C. Chunxi Road Station
    Chunxi Road Station is a major metro station in Chengdu, China, providing access to the popular commercial and shopping district around Chunxi Road.
  • D. Xintiandi station
    Xintiandi station is a major Shanghai Metro interchange located near the popular Xintiandi entertainment and shopping district.
  • E. Dongdan Station
    Dongdan Station is a major Beijing Subway interchange station serving as a key transfer point between central city lines.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed5b8b081908d7127964eed3b09 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01953c493c819084850ab8e7f0d261 completed May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 4:15 a.m.