Triple
T13388902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château La Fleur-Pétrus |
E319519
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Libournais |
E313294
|
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: Libournais | Statement: [Château La Fleur-Pétrus, locatedIn, Libournais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Libournais Context triple: [Château La Fleur-Pétrus, locatedIn, Libournais]
-
A.
Libournais
chosen
Libournais is a renowned wine-producing region on Bordeaux’s Right Bank in southwestern France, known for its Merlot-dominant red wines and appellations such as Pomerol and Saint-Émilion.
-
B.
Aixois
Aixois is the French demonym for inhabitants of the spa town of Aix-les-Bains in southeastern France.
-
C.
Lyonnais
Lyonnais is a historical region in east-central France centered around the city of Lyon, known for its rich cultural heritage, gastronomy, and role as a major economic hub.
-
D.
Loulé
Loulé is a historic market town and municipality in southern Portugal known for its traditional architecture, lively festivals, and role as a cultural and commercial center in the Algarve region.
-
E.
Donin
Donin is a surname that appears as a variant spelling of Donen.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d3a40081909ba49556130ad0e7 |
completed | April 12, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f72691c8d08190b971d7e914863cc1 |
completed | May 3, 2026, 10:42 a.m. |
Created at: April 9, 2026, 9:34 p.m.