Triple
T16847426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TGV Atlantique services |
E409579
|
entity |
| Predicate | primaryCityServed |
P82
|
FINISHED |
| Object | Le Mans |
E43233
|
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: Le Mans | Statement: [TGV Atlantique services, primaryCityServed, Le Mans]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Mans Context triple: [TGV Atlantique services, primaryCityServed, Le Mans]
-
A.
Le Mans
chosen
Le Mans is a historic city in northwestern France best known for its annual 24 Hours of Le Mans endurance sports car race.
-
B.
Paris–Le Mans
Paris–Le Mans is a major high-speed rail corridor in France linking the capital to the city of Le Mans as part of the TGV Atlantique network.
-
C.
Montlhéry
Montlhéry is a commune in northern France best known for its historic motor racing circuit, the Autodrome de Linas-Montlhéry.
-
D.
Viroflay
Viroflay is a suburban commune in the Yvelines department of the Île-de-France region in north-central France, located just southwest of Paris.
-
E.
Deauzya
Deauzya is the given first name of American professional basketball player DiDi Richards.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b376bac48190ae09f29a28c55f8c |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2a4c2a881908d2797f6e61792d3 |
completed | May 10, 2026, 5:38 p.m. |
Created at: April 10, 2026, 5:24 a.m.