Triple
T19251792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langres cheese |
E481408
|
entity |
| Predicate | pasteConsistency |
P48486
|
FINISHED |
| Object | creamy |
—
|
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: creamy | Statement: [Langres cheese, pasteConsistency, creamy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pasteConsistency Context triple: [Langres cheese, pasteConsistency, creamy]
-
A.
typicalSauceConsistency
Indicates that something has the usual or characteristic thickness or texture expected of a sauce.
-
B.
doughCharacteristic
Indicates that a specified quality, property, or attribute is being ascribed to a particular dough.
-
C.
isThickenedWith
Indicates that one substance has been made more viscous or dense by adding another substance that serves as a thickening agent.
-
D.
fillType
Indicates the manner or pattern in which an area, shape, or container is filled (e.g., solid, gradient, pattern, or other fill style).
-
E.
viscosity
chosen
Indicates the degree to which a fluid resists flowing or changing shape under an applied force.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb30bf6c819094c44aceb544a023 |
completed | April 20, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:28 p.m.