Triple

T15645425
Position Surface form Disambiguated ID Type / Status
Subject Bannan line E376164 entity
Predicate hasTerminus P388 FINISHED
Object Dingpu station
Dingpu station is a metro station in New Taipei City, Taiwan, serving as the western terminus of Taipei Metro’s Bannan (Blue) line.
E1170392 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: Dingpu station | Statement: [Bannan line, hasTerminus, Dingpu station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dingpu station
Context triple: [Bannan line, hasTerminus, Dingpu station]
  • A. Jinyintan Station
    Jinyintan Station is a metro station in Wuhan, China, serving passengers on the city's Line 2 rapid transit route.
  • B. Huangsha Station
    Huangsha Station is a metro station in Guangzhou, China, serving as part of the city's Guangzhou Metro rapid transit network.
  • C. Tiantongyuan station
    Tiantongyuan station is a subway station in Beijing, China, serving the northern residential area of Tiantongyuan on the city's metro network.
  • D. Xihu Station
    Xihu Station is a metro station in Taipei, Taiwan, serving the Neihu District and providing access to nearby commercial and entertainment areas.
  • E. Baiduizi station
    Baiduizi station is an underground metro stop on Beijing's extensive subway network, serving passengers in the city's urban core.
  • 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: Dingpu station
Triple: [Bannan line, hasTerminus, Dingpu station]
Generated description
Dingpu station is a metro station in New Taipei City, Taiwan, serving as the western terminus of Taipei Metro’s Bannan (Blue) line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dingpu station
Target entity description: Dingpu station is a metro station in New Taipei City, Taiwan, serving as the western terminus of Taipei Metro’s Bannan (Blue) line.
  • A. Jinyintan Station
    Jinyintan Station is a metro station in Wuhan, China, serving passengers on the city's Line 2 rapid transit route.
  • B. Huangsha Station
    Huangsha Station is a metro station in Guangzhou, China, serving as part of the city's Guangzhou Metro rapid transit network.
  • C. Tiantongyuan station
    Tiantongyuan station is a subway station in Beijing, China, serving the northern residential area of Tiantongyuan on the city's metro network.
  • D. Xihu Station
    Xihu Station is a metro station in Taipei, Taiwan, serving the Neihu District and providing access to nearby commercial and entertainment areas.
  • E. Baiduizi station
    Baiduizi station is an underground metro stop on Beijing's extensive subway network, serving passengers in the city's urban core.
  • 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_69ff6790f2288190add8ab0bc0f114bf completed May 9, 2026, 4:57 p.m.
NEDg Description generation batch_69ff6bc27ef481908f5125ab553b5015 completed May 9, 2026, 5:15 p.m.
NED2 Entity disambiguation (via description) batch_69ff6c214c7881908ac483dbb8d08f29 completed May 9, 2026, 5:17 p.m.
Created at: April 10, 2026, 4:15 a.m.