Triple
T16343259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Bordeaux high-speed rail corridor |
E396860
|
entity |
| Predicate | usedByService |
P1294
|
FINISHED |
| Object | TGV INOUI |
E766803
|
NE 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: TGV INOUI | Statement: [Paris–Bordeaux high-speed rail corridor, usedByService, TGV INOUI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TGV INOUI Context triple: [Paris–Bordeaux high-speed rail corridor, usedByService, TGV INOUI]
-
A.
TGV INOUI
chosen
TGV INOUI is SNCF’s premium high-speed train service in France, offering upgraded comfort, amenities, and service compared to standard TGV trains.
-
B.
TGV PSE
TGV PSE is the original generation of French high-speed TGV Sud-Est trainsets that inaugurated high-speed rail service in France.
-
C.
TGV
TGV is France’s high-speed intercity train service, renowned for rapid connections between major cities such as Paris and Lille.
-
D.
TGV Est
TGV Est is a French high-speed train service connecting Paris with eastern France and neighboring European countries such as Germany, Luxembourg, and Switzerland.
-
E.
TGV Ouigo
TGV Ouigo is a low-cost high-speed train service operated by SNCF in France, offering budget fares on selected TGV routes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2da0b88d081908a99cafa8e0ae5db |
completed | April 18, 2026, 1:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c4e6d548190b895a76a4a7268dd |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:07 a.m.