Triple
T9488652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mediterranean high-speed line |
E228825
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | TGV trains |
E445505
|
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 trains | Statement: [Mediterranean high-speed line, usedBy, TGV trains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TGV trains Context triple: [Mediterranean high-speed line, usedBy, TGV trains]
-
A.
TGV high-speed rail
TGV high-speed rail is France’s flagship high-speed train service that connects major cities and hubs, including direct links from Charles de Gaulle Airport to destinations across the country and into neighboring nations.
-
B.
TGV
chosen
TGV is France’s high-speed intercity train service, renowned for rapid connections between major cities such as Paris and Lille.
-
C.
TGV Ouigo
TGV Ouigo is a low-cost high-speed train service operated by SNCF in France, offering budget fares on selected TGV routes.
-
D.
TGV Réseau
TGV Réseau is a later-generation French high-speed trainset used by SNCF, designed for improved performance and comfort on the expanding TGV network.
-
E.
TGV INOUI
TGV INOUI is SNCF’s premium high-speed train service in France, offering upgraded comfort, amenities, and service compared to standard TGV trains.
- 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_69ca847424f081908180305555139f7a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd80c5a05c8190b97d34f010e60ca1 |
completed | April 1, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcaaeaa08190b90ca5600deb84a2 |
completed | April 5, 2026, 1:36 a.m. |
Created at: March 30, 2026, 7:55 p.m.