Triple
T33971666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Montpellier |
E871013
|
entity |
| Predicate | mainTerminusStation |
P151408
|
FINISHED |
| Object | Montpellier-Saint-Roch |
—
|
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: Montpellier-Saint-Roch | Statement: [Paris–Montpellier, mainTerminusStation, Montpellier-Saint-Roch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainTerminusStation Context triple: [Paris–Montpellier, mainTerminusStation, Montpellier-Saint-Roch]
-
A.
formerTerminalStation
Indicates that a location once served as the end point (terminus) of a transportation line or route but no longer holds that status.
-
B.
terminusStation
Indicates that a station serves as the final endpoint or terminal stop for a given route or service.
-
C.
railroadTerminusFor
Indicates that one location serves as the end point or final station of a particular railroad line for another location.
-
D.
railwayUpperTerminus
Indicates that a railway line or route reaches its upper (typically higher-altitude or upstream) terminal endpoint at the related location.
-
E.
railTerminusFor
chosen
Indicates that one location serves as the final or terminal rail station or endpoint for a specified rail line or service.
- 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_69f3499da0188190ab1a4ff06fb06a2a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 1, 2026, 1:50 a.m.