Triple
T31507191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Chênes de Bouscaut (red) |
E803849
|
entity |
| Predicate | belongsToEstateRange |
P70713
|
FINISHED |
| Object |
Les Chênes de Bouscaut
Les Chênes de Bouscaut is a Bordeaux wine produced as a second label of the historic Château Bouscaut estate in the Pessac-Léognan appellation.
|
E1965589
|
NE FINISHED |
How this triple was built (3 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: Les Chênes de Bouscaut | Statement: [Les Chênes de Bouscaut (red), belongsToEstateRange, Les Chênes de Bouscaut]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Les Chênes de Bouscaut Triple: [Les Chênes de Bouscaut (red), belongsToEstateRange, Les Chênes de Bouscaut]
Generated description
Les Chênes de Bouscaut is a Bordeaux wine produced as a second label of the historic Château Bouscaut estate in the Pessac-Léognan appellation.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToEstateRange Context triple: [Les Chênes de Bouscaut (red), belongsToEstateRange, Les Chênes de Bouscaut]
-
A.
hasAssociatedEstate
Indicates that one entity is linked to, or has responsibility for, a particular estate or property.
-
B.
memberOfEstateSystem
chosen
Indicates that an entity belongs to, is included within, or is administered as part of a particular estate system.
-
C.
hasEstateType
Indicates that an entity possesses or is associated with a particular category or type of estate.
-
D.
hasNeighbouringEstate
Indicates that one estate is directly adjacent to or shares a boundary with another estate.
-
E.
hasEstateManager
Indicates that an entity is responsible for managing, overseeing, or administering the estate or property of another entity.
- F. None of above.
Provenance (6 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2b147306248190b8be73d3b90527d1 |
completed | June 11, 2026, 8:02 p.m. |
| NEDg | Description generation | batch_6a2b1631ffcc8190bf1c512953e526f6 |
completed | June 11, 2026, 8:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a2b18c22a48819084a8414aee86ca35 |
completed | June 11, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: April 30, 2026, 9:48 p.m.