Triple
T14288349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Plagne |
E354237
|
entity |
| Predicate | nearestCity |
P350
|
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: [La Plagne, nearestCity, Aime]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aime Context triple: [La Plagne, nearestCity, 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.
Durolle
Durolle is a river in central France that flows through the town of Thiers, historically powering its renowned cutlery and knife-making industry.
-
C.
Aimes
Aimes is a character appearing in the action film "Fast X" from the Fast & Furious franchise.
-
D.
Fourvière
Fourvière is a prominent hill in Lyon, France, known for its basilica, panoramic views over the city, and historical significance as a major religious and cultural site.
-
E.
Taine
Taine was a notable philhellene recognized for his strong support and admiration of Greek culture and independence.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de698023288190b1d705235c2b2ca3 |
completed | April 14, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d1e14d4819091c381f96c43c58b |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:11 a.m.