Triple
T3711123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kishimen noodles |
E81411
|
entity |
| Predicate | typicalCookingTime |
P50957
|
FINISHED |
| Object | shorter than round udon noodles |
—
|
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: shorter than round udon noodles | Statement: [kishimen noodles, typicalCookingTime, shorter than round udon noodles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCookingTime Context triple: [kishimen noodles, typicalCookingTime, shorter than round udon noodles]
-
A.
ripeningTime
Indicates the period or duration required for something to become fully ripe or reach its mature, ready-to-use state.
-
B.
requiresCookingTemperature
Indicates that performing the action or preparing the item necessitates reaching or maintaining a specific cooking temperature.
-
C.
typicalPreparation
Indicates the usual or standard way in which something is prepared or made.
-
D.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
E.
meatPreparation
Indicates the method or process by which meat is treated, cooked, or otherwise prepared for consumption.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc58617bc8190bb712d1c90394215 |
completed | March 8, 2026, 6:52 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc133ef50819094c2b971f31f1615 |
completed | March 8, 2026, 6:34 p.m. |
Created at: March 8, 2026, 3:33 p.m.