Triple
T9178897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Torta del Casar |
E220269
|
entity |
| Predicate | vegetableRennetSource |
P86679
|
FINISHED |
| Object | cardoon (Cynara cardunculus) |
—
|
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: cardoon (Cynara cardunculus) | Statement: [Torta del Casar, vegetableRennetSource, cardoon (Cynara cardunculus)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vegetableRennetSource Context triple: [Torta del Casar, vegetableRennetSource, cardoon (Cynara cardunculus)]
-
A.
cheeseMadeFrom
Indicates that one entity is produced or derived as cheese from another entity (typically a source ingredient such as milk).
-
B.
isLegume
Indicates that something belongs to the group of plants classified as legumes, typically producing seeds in pods and often associated with nitrogen-fixing properties.
-
C.
isVegetarian
Indicates that an entity follows a vegetarian diet, avoiding the consumption of meat and possibly other animal products.
-
D.
edibleSpecies
Indicates that one species can be safely eaten as food by another species or by humans.
-
E.
ediblePart
Indicates that one entity is a part of another entity that can be eaten or consumed.
- 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_69ca83e589948190ac9907819db11ddf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc25064588190856c96b229d9cd60 |
completed | April 1, 2026, 6:59 a.m. |
| PD | Predicate disambiguation | batch_69cc66090e5881908889dc1213815626 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc66d7bf648190b8bff5b584b84975 |
completed | April 1, 2026, 12:29 a.m. |
Created at: March 30, 2026, 7:23 p.m.