Triple
T169549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Okonomiyaki |
E3088
|
entity |
| Predicate | hasMainIngredient |
P5291
|
FINISHED |
| Object | wheat flour |
—
|
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: wheat flour | Statement: [Okonomiyaki, hasMainIngredient, wheat flour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainIngredient Context triple: [Okonomiyaki, hasMainIngredient, wheat flour]
-
A.
hasMainOrgan
Indicates that an entity possesses a primary or principal organ that plays a central role in its biological or functional system.
-
B.
isLegume
Indicates that something belongs to the group of plants classified as legumes, typically producing seeds in pods and often associated with nitrogen-fixing properties.
-
C.
hasPrimaryFunction
Indicates that one entity serves as the main or principal function or role of another entity.
-
D.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
E.
hasDietaryLaw
Indicates that one entity prescribes, follows, or is governed by a specific set of dietary rules or restrictions associated with another entity.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258b6f4f88190b1264bbbeb19a29e |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25665f5b8819096ca3e084faf976e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25710bdfc81909b6697159104cf53 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.