Triple
T22180562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French railway network |
E548156
|
entity |
| Predicate | mainHighSpeedService |
P35275
|
FINISHED |
| Object | OUIGO |
—
|
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: OUIGO | Statement: [French railway network, mainHighSpeedService, OUIGO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OUIGO Context triple: [French railway network, mainHighSpeedService, OUIGO]
-
A.
OUIGO
chosen
OUIGO is a low-cost high-speed train service operated by France’s national railway company SNCF, offering budget-friendly travel on major routes.
-
B.
SNCF
SNCF is France’s national state-owned railway company, responsible for operating the country’s passenger and freight rail services and much of its rail infrastructure.
-
C.
SNCF Réseau
SNCF Réseau is the French state-owned rail infrastructure manager responsible for operating, maintaining, and developing France’s national railway network.
-
D.
Francorail
Francorail was a French railway manufacturing consortium known for producing high-speed trainsets, including early models of the TGV.
-
E.
SNCF Gares & Connexions
SNCF Gares & Connexions is the branch of the French national railway company responsible for managing and developing railway stations across France.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3d53f88190a2b690e3f25bb062 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aa4d4ac8190922b919c15623963 |
completed | April 28, 2026, 9:46 p.m. |
Created at: April 16, 2026, 8:35 p.m.