Triple
T4184472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aude |
E88276
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Hérault |
E97297
|
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: Hérault | Statement: [Aude, borders, Hérault]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hérault Context triple: [Aude, borders, Hérault]
-
A.
Hérault
chosen
Hérault is a department in southern France known for its Mediterranean coastline, vineyards, and historic cities such as Montpellier and Béziers.
-
B.
Bouches-du-Rhône
Bouches-du-Rhône is a department in southern France known for the city of Marseille, its Mediterranean coastline, and parts of the historic Provence region.
-
C.
Lozère
Lozère is a sparsely populated department in southern France known for its rugged landscapes, including parts of the Cévennes and numerous river valleys.
-
D.
Aveyron
Aveyron is a rural department in southern France known for its rugged landscapes, medieval villages, and traditional gastronomy including Roquefort cheese.
-
E.
Rouergue
Rouergue is a historic cultural region in southern France, centered around the present-day Aveyron department and known for its rural landscapes, medieval towns, and Occitan heritage.
- 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_69aed9477e8c81908bcb862d2db55b1d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0321eee88190871c1d4bf44a5007 |
completed | March 9, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b589fe4b508190a1c5a1d426245ede |
completed | March 14, 2026, 4:17 p.m. |
Created at: March 9, 2026, 3:45 p.m.