Triple

T16930664
Position Surface form Disambiguated ID Type / Status
Subject Wudaokou E410697 entity
Predicate hasTransportInfrastructure P2560 FINISHED
Object Wudaokou 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: Wudaokou station | Statement: [Wudaokou, hasTransportInfrastructure, Wudaokou station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wudaokou station
Context triple: [Wudaokou, hasTransportInfrastructure, Wudaokou station]
  • A. Wudaokou station chosen
    Wudaokou station is a busy Beijing Subway stop in the Haidian District, known for serving a major university and tech hub area popular with students and young professionals.
  • B. Wukesong station
    Wukesong station is a Beijing Subway station in the Haidian District that serves the busy Wukesong area, known for its nearby sports, entertainment, and commercial facilities.
  • C. Lianglukou Station
    Lianglukou Station is a major interchange station on the Chongqing Metro system in Chongqing, China, serving as a key hub for urban rail transit.
  • D. Zhushikou station
    Zhushikou station is a Beijing Subway interchange station in central Beijing, serving as a key stop near the historic Qianmen and Dashilan areas.
  • E. Lujiazui station
    Lujiazui station is a major Shanghai Metro stop serving the city’s key financial district in Pudong.
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cf248c6c81908fbf4d49e5381f08 completed April 18, 2026, 6:36 p.m.
Created at: April 10, 2026, 5:30 a.m.