Triple
T9386696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cru Bourgeois |
E225921
|
entity |
| Predicate | productionArea |
P3992
|
FINISHED |
| Object | Moulis-en-Médoc |
E241352
|
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: Moulis-en-Médoc | Statement: [Cru Bourgeois, productionArea, Moulis-en-Médoc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moulis-en-Médoc Context triple: [Cru Bourgeois, productionArea, Moulis-en-Médoc]
-
A.
Moulis-en-Médoc
chosen
Moulis-en-Médoc is a Bordeaux wine-producing commune in southwestern France, known for its red wines within the Médoc region.
-
B.
Lesparre-Médoc
Lesparre-Médoc is a small commune in southwestern France, situated in the Médoc region and known for its wine-producing surroundings and historic town center.
-
C.
Mérignac
Mérignac is a suburban city in southwestern France, forming part of the Bordeaux metropolitan area and hosting the region’s main international airport.
-
D.
Ribérac
Ribérac is a small historic town in southwestern France’s Dordogne department, known for its traditional markets and rural charm.
-
E.
Figeac
Figeac is a historic town in southwestern France known for its medieval architecture and as the birthplace of Jean-François Champollion, who deciphered Egyptian hieroglyphs.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d3964c8190b0353f56df755db8 |
completed | April 1, 2026, 5:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1101e83e8819093fe8d25c819820b |
completed | April 4, 2026, 1:20 p.m. |
Created at: March 30, 2026, 7:45 p.m.