Triple
T15645647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhongxiao Xinsheng |
E376168
|
entity |
| Predicate | isKeyStationIn |
P30882
|
FINISHED |
| Object | central Taipei |
—
|
LITERAL 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: central Taipei | Statement: [Zhongxiao Xinsheng, isKeyStationIn, central Taipei]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isKeyStationIn Context triple: [Zhongxiao Xinsheng, isKeyStationIn, central Taipei]
-
A.
isLocalStationFor
Indicates that a station serves a specific local area or locality as its primary service point.
-
B.
hasStationAt
Indicates that an entity maintains or operates a station located at a specified place.
-
C.
isLocalStation
Indicates that a station operates primarily within a limited local area or serves as a stop on a local (rather than regional or long-distance) service.
-
D.
isMajorStationOn
chosen
Indicates that a station serves as a primary or significant stop on a particular route or line.
-
E.
hasComponentStation
Indicates that an entity includes or is associated with a specific station as one of its component parts.
- F. None of above.
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_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.