Triple
T28219167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tatenokai |
E711401
|
entity |
| Predicate | ledByDuringIncident |
P4208
|
FINISHED |
| Object | Yukio Mishima |
—
|
NE NERFINISHED |
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: Yukio Mishima | Statement: [Tatenokai, ledByDuringIncident, Yukio Mishima]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ledByDuringIncident Context triple: [Tatenokai, ledByDuringIncident, Yukio Mishima]
-
A.
missionDuringIncident
Indicates that a mission or operation took place concurrently with, or in the context of, a specific incident.
-
B.
ledOrganizationDuring
Indicates that a person held a leadership role in an organization for a specified period of time.
-
C.
responseLedBy
Indicates that a particular response, initiative, or action is directed, coordinated, or overseen by a specified leading entity.
-
D.
leaderDuring
chosen
Indicates that one entity serves as the leader of another entity during a specified time period.
-
E.
incidentWith
Indicates that one entity is involved in, affected by, or associated with a particular incident or event together with another 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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6434f9f888190bd43fde92cd729fe |
completed | May 2, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 10:45 p.m.