Triple
T23383919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beyond Beef |
E593823
|
entity |
| Predicate | cooksSimilarTo |
P152038
|
FINISHED |
| Object | ground beef |
—
|
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: ground beef | Statement: [Beyond Beef, cooksSimilarTo, ground beef]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cooksSimilarTo Context triple: [Beyond Beef, cooksSimilarTo, ground beef]
-
A.
similarDish
Indicates that two dishes share notable similarities, such as ingredients, preparation methods, flavor profile, or style.
-
B.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
-
C.
sharesCuisineWith
Indicates that two entities offer or are associated with the same type or style of cuisine.
-
D.
isUsuallyCookedIn
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
E.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a496ae34819090e86c89eef6d2dc |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:34 p.m.