Triple

T3161853
Position Surface form Disambiguated ID Type / Status
Subject Batong Line E66118 entity
Predicate hasStation P35 FINISHED
Object Sihui Station E72671 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: Sihui Station | Statement: [Batong Line, hasStation, Sihui Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sihui Station
Context triple: [Batong Line, hasStation, Sihui Station]
  • A. Sihui station chosen
    Sihui station is a Beijing Subway interchange station serving as a key transfer point between major urban rail lines in the city.
  • B. Lijiao Station
    Lijiao Station is an interchange station on the Guangzhou Metro system in Guangzhou, China, serving as a local transit hub for passengers in its surrounding urban area.
  • C. Zhichunlu station
    Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
  • D. Guomao station
    Guomao station is a major interchange hub on the Beijing Subway, serving the central business district and connecting key metro lines.
  • E. Xinzhuang Station
    Xinzhuang Station is a major Shanghai Metro interchange station in Minhang District, serving as a key southern transport hub in the city’s network.
  • 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_69ad85850c1481908a9e9c6242238de2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada618b9b88190afaa6d47dcad9f2c completed March 8, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38babb044819098f887ac4fb0bab2 completed March 13, 2026, 3:59 a.m.
Created at: March 8, 2026, 3:06 p.m.