Triple
T8788436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TER Nouvelle-Aquitaine |
E209099
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object | Guéret |
E190818
|
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: Guéret | Statement: [TER Nouvelle-Aquitaine, servesCity, Guéret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guéret Context triple: [TER Nouvelle-Aquitaine, servesCity, Guéret]
-
A.
Guéret
chosen
Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
-
B.
Montluçon
Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
-
C.
Chapeauroux
Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
-
D.
Beaucaire
Beaucaire is a historic town in southern France known for its medieval architecture and its location along the Rhône River.
-
E.
Aurillac
Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making industry.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f89a84c819085d4cfe4e6dfbda8 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffd6b7eb88190b878165e41cf1df8 |
completed | April 3, 2026, 5:48 p.m. |
Created at: March 30, 2026, 6:43 p.m.