Triple
T4958307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarentaise Valley |
E111340
|
entity |
| Predicate | notableTown |
P14082
|
FINISHED |
| Object | Aime |
E483100
|
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: Aime | Statement: [Tarentaise Valley, notableTown, Aime]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aime Context triple: [Tarentaise Valley, notableTown, Aime]
-
A.
Aime
chosen
Aime is a small town in the French Alps known as a gateway to the Tarentaise Valley’s major ski resorts.
-
B.
Taine
Taine was a notable philhellene recognized for his strong support and admiration of Greek culture and independence.
-
C.
Valleiry
Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
-
D.
Peillon
Peillon is a picturesque medieval hilltop village in southeastern France, known for its narrow streets, stone houses, and views over the surrounding Alpes-Maritimes countryside.
-
E.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71d834c0819087f3faafdc9b4228 |
completed | March 20, 2026, 4:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be89f639c081908658c1a228081dd9 |
completed | March 21, 2026, 12:07 p.m. |
Created at: March 20, 2026, 1:32 p.m.