Triple
T169553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Okonomiyaki |
E3088
|
entity |
| Predicate | hasTypicalIngredient |
P35
|
FINISHED |
| Object | green onion |
—
|
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: green onion | Statement: [Okonomiyaki, hasTypicalIngredient, green onion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalIngredient Context triple: [Okonomiyaki, hasTypicalIngredient, green onion]
-
A.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
B.
includesBowl
Indicates that something contains or has a bowl as one of its components or elements.
-
C.
hasPart
chosen
Indicates that one entity is a component, segment, or constituent part of another entity.
-
D.
typicalCountryIncluded
Indicates that a country is commonly or characteristically included within a given grouping, context, or set.
-
E.
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.
- 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_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. |
Created at: Feb. 28, 2026, 2:34 a.m.