Triple
T9288120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bourgogne Aligoté AOC |
E223447
|
entity |
| Predicate | labelIndication |
P87420
|
FINISHED |
| Object | must state Bourgogne Aligoté |
—
|
LITERAL 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: must state Bourgogne Aligoté | Statement: [Bourgogne Aligoté AOC, labelIndication, must state Bourgogne Aligoté]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelIndication Context triple: [Bourgogne Aligoté AOC, labelIndication, must state Bourgogne Aligoté]
-
A.
labelOf
Indicates that one entity serves as the name, tag, or identifying label assigned to another entity.
-
B.
labelDepicts
Indicates that one entity serves as a label or caption that visually or textually represents, illustrates, or describes another entity.
-
C.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
-
D.
labelLocation
Indicates that a label or identifier is associated with a specific spatial or geographic location.
-
E.
labelMate
Indicates that two entities are associated with the same label, such as being signed to or represented by the same organization, brand, or record label.
- F. None of above. chosen
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_69ca8422ddf881908a3f8f876c9f53aa |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0861425c81909e3ab11e19cc2f65 |
completed | April 1, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69cc7a576ec88190bbb787eb82e2e539 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc94b796788190816b71b1e9996288 |
completed | April 1, 2026, 3:44 a.m. |
Created at: March 30, 2026, 7:35 p.m.