Triple
T19267822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wakakusa-yama |
E481834
|
entity |
| Predicate | YamayakiFeatures |
P135363
|
FINISHED |
| Object | burning of the hillside grass |
—
|
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: burning of the hillside grass | Statement: [Wakakusa-yama, YamayakiFeatures, burning of the hillside grass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: YamayakiFeatures Context triple: [Wakakusa-yama, YamayakiFeatures, burning of the hillside grass]
-
A.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
B.
ehomakiCustom
Indicates a customized or personalized way of preparing, filling, or presenting ehomaki (a traditional sushi roll), differing from the standard or conventional style.
-
C.
heatingMethod
Indicates the method or technique used to apply heat to something, such as for cooking, warming, or processing.
-
D.
honkanStyle
Indicates a relationship where something follows or exhibits the characteristics of the Honkan style (a specific stylistic or design convention).
-
E.
servesDish
Indicates that one entity prepares and presents a specific dish as food for 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb8e1f888190a95f60fa29ca3b98 |
completed | April 20, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4df51ac6c819091ce72b07790ffa6 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:29 p.m.