Triple
T12284632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Martini |
E292796
|
entity |
| Predicate | secondaryFruitNote |
P71397
|
FINISHED |
| Object | raspberry |
—
|
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: raspberry | Statement: [French Martini, secondaryFruitNote, raspberry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryFruitNote Context triple: [French Martini, secondaryFruitNote, raspberry]
-
A.
secondaryGrape
Indicates that one grape variety serves as a secondary or supporting component in a wine blend relative to the primary grape.
-
B.
secondaryAroma
chosen
Indicates that an entity has a secondary or supporting aroma characteristic in addition to its primary scent.
-
C.
secondaryWine
Indicates a relationship where one wine is designated as a secondary or supporting wine in relation to a primary wine.
-
D.
secondaryFood
Indicates that one entity serves as a secondary or supplementary food source in relation to another entity.
-
E.
fruitCharacteristic
Indicates that a specified characteristic or property is attributed to a particular fruit.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.