Triple
T36527160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château Tour Léognan (red) |
E900336
|
entity |
| Predicate | locatedInVineyardAreaOf |
P45203
|
FINISHED |
| Object | Pessac-Léognan |
E50052
|
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: Pessac-Léognan | Statement: [Château Tour Léognan (red), locatedInVineyardAreaOf, Pessac-Léognan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInVineyardAreaOf Context triple: [Château Tour Léognan (red), locatedInVineyardAreaOf, Pessac-Léognan]
-
A.
hasVineyardsNear
Indicates that one entity possesses or is associated with vineyards located in close geographic proximity to another entity.
-
B.
vineyardLocation
chosen
Indicates the geographical place where a vineyard is situated or established.
-
C.
traditionalVineyardArea
Indicates the area of land that is used as a traditional vineyard, typically cultivated with long-established grape-growing practices.
-
D.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
E.
alsoProducesWineIn
Indicates that the subject, in addition to other products or activities, produces wine in the specified location or context.
- F. None of above.
Provenance (4 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_69f76e5eedb88190a393b8c623f71dd7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40636e6ad08190a06a044a7b91122a |
completed | June 27, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.