Triple
T24790300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 東北福祉大学 |
E620232
|
entity |
| Predicate | スポーツの特色 |
P6214
|
FINISHED |
| Object | 硬式野球部が強豪として知られている |
—
|
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: 硬式野球部が強豪として知られている | Statement: [東北福祉大学, スポーツの特色, 硬式野球部が強豪として知られている]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: スポーツの特色 Context triple: [東北福祉大学, スポーツの特色, 硬式野球部が強豪として知られている]
-
A.
competitionCharacteristic
Indicates that a specific characteristic, feature, or attribute is associated with a competition, describing some quality or property of that competitive event or context.
-
B.
traditionalSport
Indicates that an entity is a sport practiced within a culture or community that has been passed down over generations and is recognized as part of traditional or heritage activities.
-
C.
popularSport
Indicates that a sport is widely liked, followed, or played by many people within a certain group or region.
-
D.
sportCreated
Indicates that an entity is the originator or inventor of a particular sport.
-
E.
sportFocus
chosen
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
- 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f41102028081909cde16f6e80bc321 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:47 a.m.