Triple
T12144352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Givry |
E289276
|
entity |
| Predicate | typicalStyleRed |
P103599
|
FINISHED |
| Object | medium-bodied |
—
|
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: medium-bodied | Statement: [Givry, typicalStyleRed, medium-bodied]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalStyleRed Context triple: [Givry, typicalStyleRed, medium-bodied]
-
A.
typicalRedStyleDescriptor
Indicates that something is described as having the characteristic or stylistic qualities typically associated with the color red.
-
B.
styleRed
Indicates that an entity has a red visual style or is presented using a red-themed appearance.
-
C.
typicalRedProfile
Indicates that an entity exhibits a characteristic or standard pattern commonly associated with the color red.
-
D.
typicalVisualStyle
Indicates the characteristic or commonly observed visual appearance or aesthetic style associated with an entity.
-
E.
traditionalStyle
Indicates that something follows or embodies a conventional, long-established way of doing, making, or presenting it, in contrast to modern or innovative styles.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d9183ec1008190b437b7d5e1f52830 |
completed | April 10, 2026, 3:33 p.m. |
Created at: April 8, 2026, 9:49 p.m.