Triple
T4014595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gard |
E90724
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Ardèche |
E62464
|
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: Ardèche | Statement: [Gard, borders, Ardèche]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ardèche Context triple: [Gard, borders, Ardèche]
-
A.
Ardèche
chosen
Ardèche is a department in southeastern France known for its dramatic river gorges, limestone caves, and scenic rural landscapes.
-
B.
Isère
Isère is a department in southeastern France known for its Alpine landscapes, winter sports resorts, and the city of Grenoble.
-
C.
Ardèche River
The Ardèche River is a scenic waterway in south-central France renowned for its dramatic limestone gorges, natural stone arch (Pont d’Arc), and popular canoeing and kayaking routes.
-
D.
Ariège
Ariège is a river in southwestern France that flows through the Pyrenees before joining the Garonne.
-
E.
Ariège
Ariège is a department in southwestern France, known for its Pyrenean landscapes, medieval castles, and rich Occitan culture.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaa5afdc8190b709af2473d75d02 |
completed | March 9, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea45c53908190af21d54dbf9550f0 |
completed | March 21, 2026, 1:59 p.m. |
Created at: March 9, 2026, 3:35 p.m.