Triple

T15645447
Position Surface form Disambiguated ID Type / Status
Subject Bannan line E376164 entity
Predicate hasStation P35 FINISHED
Object Kunyang station
Kunyang station is a metro station on the Taipei Metro system in Taiwan, serving the Bannan line in the Nangang District.
E1257470 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: Kunyang station | Statement: [Bannan line, hasStation, Kunyang station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kunyang station
Context triple: [Bannan line, hasStation, Kunyang station]
  • A. Yongning station
    Yongning station is a metro station on Taipei's Bannan (Blue) Line serving the Tucheng District in New Taipei City, Taiwan.
  • B. Kengkou station
    Kengkou station is a metro station on the Guangzhou Metro network in Guangzhou, China.
  • C. 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.
  • D. Chegongzhuang station
    Chegongzhuang station is a Beijing Subway interchange station serving Line 2 and Line 6 in the Xicheng District of central Beijing.
  • E. Zhichunlu station
    Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
  • 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: Kunyang station
Triple: [Bannan line, hasStation, Kunyang station]
Generated description
Kunyang station is a metro station on the Taipei Metro system in Taiwan, serving the Bannan line in the Nangang District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kunyang station
Target entity description: Kunyang station is a metro station on the Taipei Metro system in Taiwan, serving the Bannan line in the Nangang District.
  • A. Yongning station
    Yongning station is a metro station on Taipei's Bannan (Blue) Line serving the Tucheng District in New Taipei City, Taiwan.
  • B. Kengkou station
    Kengkou station is a metro station on the Guangzhou Metro network in Guangzhou, China.
  • C. 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.
  • D. Chegongzhuang station
    Chegongzhuang station is a Beijing Subway interchange station serving Line 2 and Line 6 in the Xicheng District of central Beijing.
  • E. Zhichunlu station
    Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed400ec8190a14a9f7cf3092865 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0167369d9481909015c34d475fac14 completed May 11, 2026, 5:20 a.m.
NEDg Description generation batch_6a0169aeaa248190b955490c62b763a1 completed May 11, 2026, 5:31 a.m.
NED2 Entity disambiguation (via description) batch_6a016a103ec0819083dd6cf5af5a20ee completed May 11, 2026, 5:33 a.m.
Created at: April 10, 2026, 4:15 a.m.