Triple

T15665356
Position Surface form Disambiguated ID Type / Status
Subject Wenhu line E377171 entity
Predicate hasStation P35 FINISHED
Object Neihu station
Neihu station is a metro station on the Taipei Metro system in Taipei, Taiwan, serving the Neihu District along the Wenhu (Brown) line.
 E1285760 NE FINISHED

How this triple was built (4 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: Neihu station | Statement: [Wenhu line, hasStation, Neihu station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Neihu station
Context triple: [Wenhu line, hasStation, Neihu station]
  • A. Zuoying Station
    Zuoying Station is a major transportation hub in Kaohsiung, Taiwan, serving high-speed rail, conventional rail, and metro services.
  • B. Jiantan Station
    Jiantan Station is a Taipei Metro station in Taiwan that serves as a major access point for visitors to the popular Shilin Night Market.
  • C. Huanbei Station
    Huanbei Station is a metro station in Taoyuan, Taiwan, serving as one end of the Taoyuan Airport MRT line and providing access to the surrounding urban area.
  • D. Luyuan station
    Luyuan station is a subway station on Beijing's Line 8 serving passengers in the city's urban transit network.
  • E. Liyuan Station
    Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Neihu station
Triple: [Wenhu line, hasStation, Neihu station]
Generated description
Neihu station is a metro station on the Taipei Metro system in Taipei, Taiwan, serving the Neihu District along the Wenhu (Brown) line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Neihu station
Target entity description: Neihu station is a metro station on the Taipei Metro system in Taipei, Taiwan, serving the Neihu District along the Wenhu (Brown) line.
  • A. Zuoying Station
    Zuoying Station is a major transportation hub in Kaohsiung, Taiwan, serving high-speed rail, conventional rail, and metro services.
  • B. Jiantan Station
    Jiantan Station is a Taipei Metro station in Taiwan that serves as a major access point for visitors to the popular Shilin Night Market.
  • C. Huanbei Station
    Huanbei Station is a metro station in Taoyuan, Taiwan, serving as one end of the Taoyuan Airport MRT line and providing access to the surrounding urban area.
  • D. Luyuan station
    Luyuan station is a subway station on Beijing's Line 8 serving passengers in the city's urban transit network.
  • E. Liyuan Station
    Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
  • F. None of above. chosen

Provenance (5 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f0f4df08190ad2c5d78e435d8eb completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0242d952988190b9b3eaca8fa92431 completed May 11, 2026, 8:58 p.m.
NEDg Description generation batch_6a0246f31c8c819097685337f0f14dad completed May 11, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_6a02478d775c8190ac9d14bd260e7eca completed May 11, 2026, 9:18 p.m.
Created at: April 10, 2026, 4:16 a.m.