Triple
T18889433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bagel |
E462042
|
entity |
| Predicate | hasTypicalTextureContrast |
P108941
|
FINISHED |
| Object | Chewy interior and slightly crisp exterior |
—
|
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: Chewy interior and slightly crisp exterior | Statement: [Bagel, hasTypicalTextureContrast, Chewy interior and slightly crisp exterior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalTextureContrast Context triple: [Bagel, hasTypicalTextureContrast, Chewy interior and slightly crisp exterior]
-
A.
textureContrast
chosen
Indicates a relationship where two surfaces or regions differ noticeably in their tactile or visual texture qualities.
-
B.
hasDensityContrast
Indicates that one entity differs from another in material density, highlighting a contrast in how compact or dense they are.
-
C.
typicalTexture
Indicates the usual or characteristic surface feel or consistency that is commonly associated with an entity.
-
D.
providesContrastWith
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
-
E.
hasMainContrast
Indicates a primary opposing or differing relationship between two elements, highlighting the main point of contrast between them.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c479f3208190a9d665865c4b630b |
completed | April 20, 2026, 6:15 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e27e1481908a8da10b28f07875 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:58 a.m.