Triple
T29916014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cantonese stir-fried water spinach with fermented bean curd |
E759796
|
entity |
| Predicate | commonCookingTool |
P173840
|
FINISHED |
| Object | wok |
—
|
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: wok | Statement: [Cantonese stir-fried water spinach with fermented bean curd, commonCookingTool, wok]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonCookingTool Context triple: [Cantonese stir-fried water spinach with fermented bean curd, commonCookingTool, wok]
-
A.
cookingAppliance
chosen
Indicates that one entity is an appliance used by another entity for cooking food.
-
B.
eatenWithUtensil
Indicates that something was eaten using a specific utensil as the means of consumption.
-
C.
isToolOf
Indicates that one entity functions as an instrument or means used by another entity to perform tasks or achieve goals.
-
D.
cookingSurface
Indicates that one entity serves as the surface or area on which another entity is used for cooking.
-
E.
dishType
Indicates the classification of a dish according to its culinary category or role (e.g., appetizer, main course, dessert).
- 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_69f2246189fc8190996b63ee1f9a2374 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: April 29, 2026, 6:12 p.m.