Triple
T493739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iwakura Mission |
E10243
|
entity |
| Predicate | longTermOutcome |
P1421
|
FINISHED |
| Object | provided extensive data for domestic reforms in Japan |
—
|
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: provided extensive data for domestic reforms in Japan | Statement: [Iwakura Mission, longTermOutcome, provided extensive data for domestic reforms in Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longTermOutcome Context triple: [Iwakura Mission, longTermOutcome, provided extensive data for domestic reforms in Japan]
-
A.
historicalOutcome
chosen
Indicates the result or consequence that an event, action, or situation produced in a historical context.
-
B.
supportsOutcome
Indicates that one entity contributes to enabling, sustaining, or improving the achievement of a particular outcome associated with another entity.
-
C.
lifespan
Indicates the duration of time between an entity’s birth (or creation) and its death (or end).
-
D.
programOutcome
Indicates the resulting state, effect, or consequence produced by executing or completing a program.
-
E.
after
Indicates that one event, state, or action occurs later in time than another, following it in temporal order.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f0fbfa408190aeb3b93996a35c00 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf90ca88190b6a182e5b6733612 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.