Triple
T37278734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemins de fer de l'État |
E925319
|
entity |
| Predicate | railNetworkDirection |
P120426
|
FINISHED |
| Object | west of Paris |
—
|
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: west of Paris | Statement: [Chemins de fer de l'État, railNetworkDirection, west of Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railNetworkDirection Context triple: [Chemins de fer de l'État, railNetworkDirection, west of Paris]
-
A.
railwayRouteDirection
chosen
Indicates the direction or orientation in which a railway route runs or is intended to be traveled.
-
B.
railwayTrafficDirection
Indicates the customary side of the track on which trains are operated or expected to run within a given railway system or segment.
-
C.
railNetworkSide
Indicates on which side of a rail network (e.g., left or right relative to a reference direction) an entity is located or associated.
-
D.
transportDirection
Indicates the directional flow or route along which something is transported from an origin toward a destination.
-
E.
trainNumberDirection
Indicates the specific direction in which a train, identified by its train number, is traveling or scheduled to travel.
- 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_69f76eafe20c8190856d3b996a4c31a7 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.