Triple
T38468171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abondance cheese |
E912631
|
entity |
| Predicate | curdCooking |
P171903
|
FINISHED |
| Object | lightly cooked |
—
|
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: lightly cooked | Statement: [Abondance cheese, curdCooking, lightly cooked]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: curdCooking Context triple: [Abondance cheese, curdCooking, lightly cooked]
-
A.
curdType
Indicates the specific kind or category of curd associated with an entity.
-
B.
cheeseMadeFrom
Indicates that one entity is produced or derived as cheese from another entity (typically a source ingredient such as milk).
-
C.
traditionalCheese
Indicates that something is recognized as a cheese made according to established, customary, or historically rooted methods or styles.
-
D.
curdTechnology
chosen
Indicates a relationship where a particular technology is used in, enables, or characterizes the process of making or handling curd.
-
E.
cheeseType
Indicates that one entity is a specific type or variety of cheese in relation to another entity.
- 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_69f76e861d8c81908559031dc66e3c15 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcd313e61c8190b174b331365b803f |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:31 p.m.