Triple
T36659072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coteaux du Vendômois AOC |
E905071
|
entity |
| Predicate | primaryRoséGrape |
P975
|
FINISHED |
| Object | Pineau d’Aunis |
E261674
|
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: Pineau d’Aunis | Statement: [Coteaux du Vendômois AOC, primaryRoséGrape, Pineau d’Aunis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryRoséGrape Context triple: [Coteaux du Vendômois AOC, primaryRoséGrape, Pineau d’Aunis]
-
A.
primaryGrapeVariety
chosen
Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
-
B.
primaryGrapeFamily
Indicates that one grape variety belongs to, or is classified under, a broader primary grape family.
-
C.
grapeColorForRosé
Indicates that a particular grape color is used in the production of rosé wine.
-
D.
grapeVarietyType
Indicates the specific type or classification of a grape variety used or referred to in a given context.
-
E.
grapeVarietal
Indicates that one entity is a specific type or variety of grape used in wine or grape production in relation to another entity.
- 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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3d1786d8e081908c7e222c632b4783 |
completed | June 25, 2026, 11:56 a.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.