Triple
T6523295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barolo |
E151240
|
entity |
| Predicate | secondaryAroma |
P71397
|
FINISHED |
| Object | red fruit |
—
|
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: red fruit | Statement: [Barolo, secondaryAroma, red fruit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryAroma Context triple: [Barolo, secondaryAroma, red fruit]
-
A.
secondaryGrape
Indicates that one grape variety serves as a secondary or supporting component in a wine blend relative to the primary grape.
-
B.
secondaryTone
Indicates that one tone functions as a secondary or supporting tonal element in relation to a primary tone within a given context.
-
C.
secondaryWine
Indicates a relationship where one wine is designated as a secondary or supporting wine in relation to a primary wine.
-
D.
secondaryConstituent
Indicates that one entity functions as a secondary or subordinate component, element, or member within the structure or composition of another entity.
-
E.
secondaryFuel
Indicates that an entity uses or is associated with a secondary (additional or backup) fuel source in addition to its primary fuel.
- 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ad970afc81909d3231203eacf413 |
completed | March 27, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69c68abbc7148190a8270d47fe10cc31 |
completed | March 27, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69c69f362ee4819090e8fa48caef7d7d |
completed | March 27, 2026, 3:16 p.m. |
Created at: March 27, 2026, 1:45 p.m.