Triple
T35385644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyler Ledford |
E1022784
|
entity |
| Predicate | knowledgeLevelOfCuisine |
P121318
|
FINISHED |
| Object | high theoretical knowledge |
—
|
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: high theoretical knowledge | Statement: [Tyler Ledford, knowledgeLevelOfCuisine, high theoretical knowledge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knowledgeLevelOfCuisine Context triple: [Tyler Ledford, knowledgeLevelOfCuisine, high theoretical knowledge]
-
A.
knowledgeLevelAssessed
chosen
Indicates that an entity’s level of knowledge or understanding has been evaluated or measured, typically against some criteria or standard.
-
B.
knowledgeType
Indicates the specific category or nature of knowledge associated with an entity or statement (e.g., factual, procedural, conceptual).
-
C.
knownForDish
Indicates that an entity is recognized or notable for preparing, serving, or being associated with a particular dish.
-
D.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
E.
foodPreparationStyle
Indicates the manner or method by which food is prepared, cooked, or processed.
- 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794f50080819095ff3c2cefc74fea |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.