Triple
T21996506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | フィリピン・ルソン島 |
E543217
|
entity |
| Predicate | 歴史的出来事 |
P2107
|
FINISHED |
| Object | フィリピン革命の主要舞台 |
—
|
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: フィリピン革命の主要舞台 | Statement: [フィリピン・ルソン島, 歴史的出来事, フィリピン革命の主要舞台]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 歴史的出来事 Context triple: [フィリピン・ルソン島, 歴史的出来事, フィリピン革命の主要舞台]
-
A.
hasHistoricalEvent
chosen
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
B.
historicalEventsDescribed
Indicates that one entity (such as a document, text, or account) describes or recounts the historical events associated with another entity.
-
C.
contemporaryEvents
Indicates that two or more events occur in the same time period or overlap temporally.
-
D.
notableEventMentionedIn
Indicates that a particular notable event is referenced or discussed within a specified source or document.
-
E.
politicalEvent
Indicates an occurrence related to political processes, activities, or changes involving governance, power, or public policy.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12765fb0c81908f7b7acda065ee2f |
completed | April 28, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:19 p.m.