Triple
T10662487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angelico |
E251260
|
entity |
| Predicate | cultivatedInRegion |
P95212
|
FINISHED |
| Object | Bergerac |
E206236
|
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: Bergerac | Statement: [Angelico, cultivatedInRegion, Bergerac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bergerac Context triple: [Angelico, cultivatedInRegion, Bergerac]
-
A.
Bergerac
chosen
Bergerac is a notable wine-producing area in southwestern France, recognized for its diverse red, white, and dessert wines.
-
B.
Bergerac
Bergerac is a British crime drama television series set on the island of Jersey, following the cases of detective Jim Bergerac.
-
C.
Vieux-Château
Vieux-Château is a historic medieval fortress located on the Île d’Yeu off the Atlantic coast of France.
-
D.
Le Barcarès
Le Barcarès is a coastal commune in southern France on the Mediterranean Sea, known for its beaches, marina, and tourism.
-
E.
Le Guignon
Le Guignon is a poem by French writer Charles Baudelaire, included among his early poetic works.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6f31b72d081908ec8029cd9f6d814 |
completed | April 9, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a8cabc88190b430cb08ed0fc515 |
completed | April 10, 2026, 10:32 p.m. |
Created at: April 8, 2026, 9:08 p.m.