Triple
T9542703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkmen cuisine |
E230195
|
entity |
| Predicate | emphasizesCookingTechnique |
P17157
|
FINISHED |
| Object | boiling meat in broth |
—
|
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: boiling meat in broth | Statement: [Turkmen cuisine, emphasizesCookingTechnique, boiling meat in broth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emphasizesCookingTechnique Context triple: [Turkmen cuisine, emphasizesCookingTechnique, boiling meat in broth]
-
A.
foodPreparationStyle
Indicates the manner or method by which food is prepared, cooked, or processed.
-
B.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
C.
hasCookingQuality
Indicates that something possesses a particular characteristic or attribute related to cooking, such as flavor, texture, or suitability for a cooking method.
-
D.
cuisineFeature
chosen
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
E.
seasoningStyle
Indicates the characteristic way in which an item is flavored or seasoned, such as the method, intensity, or cultural style of its seasoning.
- 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e9be048190bf1f01884ff7c362 |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.