Triple
T33971685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Montpellier |
E871013
|
entity |
| Predicate | connectedToCorridor |
P5520
|
FINISHED |
| Object | Paris–Lyon high-speed corridor |
—
|
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: Paris–Lyon high-speed corridor | Statement: [Paris–Montpellier, connectedToCorridor, Paris–Lyon high-speed corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectedToCorridor Context triple: [Paris–Montpellier, connectedToCorridor, Paris–Lyon high-speed corridor]
-
A.
linkedByCorridor
Indicates that two locations are directly connected to each other by a corridor.
-
B.
hasCorridor
chosen
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
C.
onCorridorTo
Indicates that one location is directly connected to another via a corridor leading toward it.
-
D.
isPartOfCorridorSystem
Indicates that one entity forms a component or segment within a larger interconnected corridor system.
-
E.
focusesOnCorridor
Indicates that an action, attention, or process is directed specifically toward a corridor or passageway.
- 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_69ff3e1762d8819089a60e402e682817 |
completed | May 9, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69ff3d8c6f308190a0646b1432752eb8 |
completed | May 9, 2026, 1:58 p.m. |
Created at: May 1, 2026, 1:50 a.m.