Triple
T29213104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Paris rail route |
E740593
|
entity |
| Predicate | terminusStationInLondon |
P15150
|
FINISHED |
| Object | London St Pancras International railway station |
—
|
NE NERFINISHED |
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: London St Pancras International railway station | Statement: [London–Paris rail route, terminusStationInLondon, London St Pancras International railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terminusStationInLondon Context triple: [London–Paris rail route, terminusStationInLondon, London St Pancras International railway station]
-
A.
primaryLondonTerminal
Indicates that a given station serves as the main London terminal for a particular rail service or route.
-
B.
terminusStation
chosen
Indicates that a station serves as the final endpoint or terminal stop for a given route or service.
-
C.
hasLondonUndergroundStation
Indicates that a place or area contains at least one London Underground (Tube) station within its boundaries.
-
D.
londonTerminusStreet
Indicates that a street serves as a terminus (end point) for transport routes in London.
-
E.
originalLondonTerminusLocation
Indicates the location of an entity’s original terminus station in London.
- 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_69f07cba2f808190a2746477d4e8345b |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 28, 2026, 12:12 p.m.