Triple
T5331671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camembert cheese |
E123323
|
entity |
| Predicate | textureWhenYoung |
P31484
|
FINISHED |
| Object | firm and chalky in the center |
—
|
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: firm and chalky in the center | Statement: [Camembert cheese, textureWhenYoung, firm and chalky in the center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textureWhenYoung Context triple: [Camembert cheese, textureWhenYoung, firm and chalky in the center]
-
A.
texture
Indicates the surface quality or feel of an entity as perceived by touch or appearance, such as being smooth, rough, soft, or coarse.
-
B.
typicalTexture
chosen
Indicates the usual or characteristic surface feel or consistency that is commonly associated with an entity.
-
C.
textureTreatment
Indicates how an entity’s surface feel or texture has been modified, processed, or treated.
-
D.
usesTexture
Indicates that one entity employs or incorporates the texture of another entity in its appearance, design, or representation.
-
E.
fleshTexture
Indicates the tactile quality or surface feel of an entity’s flesh, such as how smooth, firm, soft, or coarse it is.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85aab0308190990626cbc9da3e21 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.