Triple
T35385645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyler Ledford |
E1022784
|
entity |
| Predicate | cookingSkill |
P182911
|
FINISHED |
| Object | incompetent |
—
|
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: incompetent | Statement: [Tyler Ledford, cookingSkill, incompetent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cookingSkill Context triple: [Tyler Ledford, cookingSkill, incompetent]
-
A.
culinaryStatus
Indicates the current state or condition of something in relation to cooking or food preparation (e.g., raw, cooked, undercooked, burnt).
-
B.
culinaryForm
Indicates the specific style, preparation method, or culinary format in which a food item or dish is presented or made.
-
C.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
D.
hasCookingQuality
Indicates that something possesses a particular characteristic or attribute related to cooking, such as flavor, texture, or suitability for a cooking method.
-
E.
cookingMedium
Indicates the substance or material (such as oil, water, or air) used to cook or heat something.
- 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_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. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: May 3, 2026, 4:03 p.m.