Triple
T24959691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harris Treaty of 1858 |
E624572
|
entity |
| Predicate | effectOnJapan |
P136616
|
FINISHED |
| Object | contributed to the end of Japan’s isolationist sakoku policy |
—
|
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: contributed to the end of Japan’s isolationist sakoku policy | Statement: [Harris Treaty of 1858, effectOnJapan, contributed to the end of Japan’s isolationist sakoku policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnJapan Context triple: [Harris Treaty of 1858, effectOnJapan, contributed to the end of Japan’s isolationist sakoku policy]
-
A.
outcomeForJapan
chosen
Indicates the result, consequence, or impact that an event, action, or situation has specifically for Japan.
-
B.
effectOnUnitedStates
Indicates the impact, influence, or consequences that something has on the United States.
-
C.
japanParticipation
Indicates Japan’s involvement or role in a particular event, activity, or organization.
-
D.
effectOnRussia
Indicates the impact or consequences that something has on Russia.
-
E.
ratingJapan
Indicates that an entity assigns or holds a rating specifically related to Japan (e.g., its products, services, or overall experience).
- 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_69e2ff23a3a88190b1b9743fe5e15f94 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 5:58 a.m.