Triple
T17840326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TGV |
E445505
|
entity |
| Predicate | route |
P5619
|
FINISHED |
| Object | Paris–Rennes |
—
|
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–Rennes | Statement: [TGV, route, Paris–Rennes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris–Rennes Context triple: [TGV, route, Paris–Rennes]
-
A.
Paris–Rennes
chosen
Paris–Rennes is a major high-speed rail corridor in France linking the capital Paris with the city of Rennes in Brittany.
-
B.
Paris–Bordeaux
Paris–Bordeaux is a major high-speed rail corridor in France connecting the capital with the southwest, known for its fast TGV services.
-
C.
Bordeaux–Paris
Bordeaux–Paris was a historic ultra-distance professional cycling race in France, renowned for its extreme length and prestige before its discontinuation.
-
D.
Paris–Clermont-Ferrand
Paris–Clermont-Ferrand is a major French intercity rail route linking the capital Paris with the central city of Clermont-Ferrand.
-
E.
Paris–Nantes
Paris–Nantes is a major high-speed rail corridor in France linking the capital Paris with the western city of Nantes.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48d2b2ea08190926ec0cf01285833 |
completed | April 19, 2026, 8:07 a.m. |
Created at: April 10, 2026, 10:16 a.m.