Triple
T2505083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allier |
E52558
|
entity |
| Predicate | flowsThroughDepartment |
P9749
|
FINISHED |
| Object | Lozère |
E93541
|
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: Lozère | Statement: [Allier, flowsThroughDepartment, Lozère]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lozère Context triple: [Allier, flowsThroughDepartment, Lozère]
-
A.
Lozère
chosen
Lozère is a sparsely populated department in southern France known for its rugged landscapes, including parts of the Cévennes and numerous river valleys.
-
B.
Drôme
Drôme is a department in southeastern France known for its diverse landscapes, historic towns, and location between the Alps and the Rhône Valley.
-
C.
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.
-
D.
Hérault
Hérault is a department in southern France known for its Mediterranean coastline, vineyards, and historic cities such as Montpellier and Béziers.
-
E.
Comtat Venaissin
Comtat Venaissin was a historic papal enclave in southeastern France that, together with Avignon, formed a key center of papal temporal power from the Middle Ages until the French Revolution.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1cec9f48190848b6129aa394ce4 |
completed | March 7, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5ce4dc2c8190a1327794ac1d1b15 |
completed | March 9, 2026, 11:51 p.m. |
Created at: March 6, 2026, 9:46 p.m.