Triple
T3865290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinning Park subway station |
E91835
|
entity |
| Predicate | hasLaterTraction |
P28917
|
FINISHED |
| Object | electric multiple units |
—
|
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: electric multiple units | Statement: [Kinning Park subway station, hasLaterTraction, electric multiple units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaterTraction Context triple: [Kinning Park subway station, hasLaterTraction, electric multiple units]
-
A.
successorTractionType
chosen
Indicates that one traction type directly follows or replaces another in a sequence or evolution of traction systems.
-
B.
hasTrail
Indicates that an entity possesses, includes, or is associated with a trail or pathway.
-
C.
gainedMomentumIn
Indicates that something increased in speed, intensity, or influence within a particular context, period, or environment.
-
D.
usedTractionType
Indicates the type of traction or drive mechanism that was employed in performing the action or operating the entity.
-
E.
hasTrend
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3a253c81909df7dc0422ff7989 |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.