Triple
T3020758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naha Tug-of-War Festival |
E82447
|
entity |
| Predicate | ropeMaterial |
P618
|
FINISHED |
| Object | rice straw |
—
|
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: rice straw | Statement: [Naha Tug-of-War Festival, ropeMaterial, rice straw]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ropeMaterial Context triple: [Naha Tug-of-War Festival, ropeMaterial, rice straw]
-
A.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
B.
material
chosen
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
C.
exteriorMaterial
Indicates the material that forms the outer surface or outer construction of an object or structure.
-
D.
streetMaterial
Indicates the material composition from which a street or road surface is made.
-
E.
languageOfMaterial
Indicates the language in which a given material, resource, or content is expressed or presented.
- 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_69ad8b1fb34081908c1b873e2b7273e1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a951e688190b3e35909affd3bfd |
completed | March 8, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69ad961c430c8190ac48f2e3c7e7c649 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.