Triple
T15998027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bordeaux (See's Candies confection) |
E388022
|
entity |
| Predicate | hasPrimaryTaste |
P90711
|
FINISHED |
| Object | sweet |
—
|
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: sweet | Statement: [Bordeaux (See's Candies confection), hasPrimaryTaste, sweet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryTaste Context triple: [Bordeaux (See's Candies confection), hasPrimaryTaste, sweet]
-
A.
hasTasteIntensity
Indicates the degree or strength of taste associated with something.
-
B.
primaryFlavor
chosen
Indicates the dominant or most characteristic taste associated with an item relative to other possible flavors.
-
C.
hasSecondaryFlavor
Indicates that an entity possesses an additional, subordinate flavor characteristic beyond its primary flavor.
-
D.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
E.
hasTastingProfile
Indicates that an entity possesses a specific flavor or sensory profile, typically describing its characteristic tastes and aromas.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4e871c819082d7b1c1eaf5b4fe |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:55 a.m.