Triple
T15645265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TRTS |
E376160
|
entity |
| Predicate | majorInterchangeStation |
P30882
|
FINISHED |
| Object | Guting Station |
E480441
|
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: Guting Station | Statement: [TRTS, majorInterchangeStation, Guting Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guting Station Context triple: [TRTS, majorInterchangeStation, Guting Station]
-
A.
Guanyinsi station
Guanyinsi station is a metro stop on Beijing’s Daxing Airport Express line serving passengers traveling between the city and Beijing Daxing International Airport.
-
B.
Ximen Station
chosen
Ximen Station is a major Taipei Metro interchange station in the Ximending shopping and entertainment district of Taipei, Taiwan.
-
C.
Weiwuying Station
Weiwuying Station is an underground metro station in Kaohsiung, Taiwan, serving the Weiwuying area and providing access to the nearby National Kaohsiung Center for the Arts.
-
D.
Xintiandi station
Xintiandi station is a major Shanghai Metro interchange located near the popular Xintiandi entertainment and shopping district.
-
E.
Gangxia station
Gangxia station is a metro station in Shenzhen, China, serving as part of the city’s rapid 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_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_6a009d232074819083f58de3ee5fbf7d |
completed | May 10, 2026, 2:58 p.m. |
Created at: April 10, 2026, 4:15 a.m.