Triple
T18350248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNÎMES |
E439647
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Nîmes |
—
|
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: Nîmes | Statement: [UNÎMES, locatedIn, Nîmes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nîmes Context triple: [UNÎMES, locatedIn, Nîmes]
-
A.
Nîmes
chosen
Nîmes is a historic city in southern France renowned for its well-preserved Roman monuments, including the Arena of Nîmes and the Maison Carrée.
-
B.
Aix-en-Provence
Aix-en-Provence is a historic and picturesque city in southern France, renowned for its Provençal charm, fountains, and as the hometown of painter Paul Cézanne.
-
C.
Marseillan
Marseillan is a coastal commune in southern France known for its historic port, oyster farming, and proximity to the Étang de Thau lagoon.
-
D.
Aigues-Mortes
Aigues-Mortes is a historic fortified town in southern France, renowned for its well-preserved medieval walls and proximity to the salt marshes of the Camargue.
-
E.
Saint-Jean-du-Gard
Saint-Jean-du-Gard is a picturesque commune in southern France known as a gateway to the Cévennes mountains and for its historical role in Protestant and rural Cévenol culture.
- 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_69d8b918221c8190a9f7b563d64ac677 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e514f7700c8190ae220de870e69304 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 10:37 a.m.