Triple

T11032944
Position Surface form Disambiguated ID Type / Status
Subject Loushanguan Road E260802 entity
Predicate hasMetroStation P522 FINISHED
Object Loushanguan Road station E271270 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: Loushanguan Road station | Statement: [Loushanguan Road, hasMetroStation, Loushanguan Road station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loushanguan Road station
Context triple: [Loushanguan Road, hasMetroStation, Loushanguan Road station]
  • A. Loushanguan Road Station chosen
    Loushanguan Road Station is a Shanghai Metro station serving the Changning District area of Shanghai, China.
  • B. Qilianshan Road station
    Qilianshan Road station is a Shanghai Metro station serving the Putuo District as part of the city's urban rapid transit network.
  • C. Lianhua Road Station
    Lianhua Road Station is a Shanghai Metro station serving the Minhang District as part of the city’s rapid transit network.
  • D. Youyi Road station
    Youyi Road station is a metro station on the Shanghai Metro network serving passengers in the Baoshan District of Shanghai, China.
  • E. Tiantong Road station
    Tiantong Road station is a Shanghai Metro station located in the Hongkou District, serving as part of the city's extensive urban rail transit 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797e650b48190967c53f54e3464ad completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a9a6db688190a740b787448d97b2 completed April 18, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:25 p.m.