Triple
T36617724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pineau d’Anjou |
E903648
|
entity |
| Predicate | regionalSynonymOf |
P14444
|
FINISHED |
| Object | Pineau d’Aunis |
—
|
NE NERFINISHED |
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: [Pineau d’Anjou, regionalSynonymOf, Pineau d’Aunis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalSynonymOf Context triple: [Pineau d’Anjou, regionalSynonymOf, Pineau d’Aunis]
-
A.
isRegionalAlternativeTo
Indicates that one entity serves as a counterpart or substitute for another within a specific geographic region or local context.
-
B.
regionallyKnownAs
chosen
Indicates that an entity is known by a particular name or designation within a specific geographic region.
-
C.
regionalVariantOf
Indicates that one entity is a version or form of another that is specific to a particular geographic region or locale.
-
D.
regionallyAssociatedWith
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
E.
regionalNickname
Indicates that one entity is an informal or colloquial name used for another entity within a specific geographic region.
- F. None of above.
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_69f76e6960e4819092047756ceb9a17e |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0027e4a59481909417b2531daaf480 |
completed | May 10, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_6a0026a42bc08190ad3322ce625a523a |
completed | May 10, 2026, 6:33 a.m. |
Created at: May 3, 2026, 4:11 p.m.