Triple
T4680601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gare d'Issoire |
E103788
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Issoire |
E103788
|
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: Issoire | Statement: [Gare d'Issoire, locatedIn, Issoire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Issoire Context triple: [Gare d'Issoire, locatedIn, Issoire]
-
A.
Issoire
chosen
Issoire is a historic town in central France’s Auvergne region, known for its Romanesque architecture and location in the valley of the Allier River.
-
B.
Tatihou
Tatihou is a small French island off the coast of Normandy known for its historic Vauban fortifications, maritime museum, and rich coastal birdlife.
-
C.
Patouès
Patouès is a regional Romance dialect of the Franco-Provençal language traditionally spoken in parts of France, Switzerland, and Italy.
-
D.
Vauvert
Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
-
E.
Vallauris
Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd636d306081908ff512896f54cb10 |
completed | March 20, 2026, 3:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be105232e88190bb79bf52b58e1814 |
completed | March 21, 2026, 3:28 a.m. |
Created at: March 20, 2026, 1:16 p.m.