Triple
T23860346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oyashio |
E592429
|
entity |
| Predicate | countryInfluenced |
P154219
|
FINISHED |
| Object | Japan |
—
|
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: Japan | Statement: [Oyashio, countryInfluenced, Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryInfluenced Context triple: [Oyashio, countryInfluenced, Japan]
-
A.
countryInfluence
Indicates the degree to which one country affects or shapes the policies, decisions, or conditions within another country or in the international arena.
-
B.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
-
C.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
D.
languageOfInfluence
Indicates a relationship where one language has influenced the development, usage, or characteristics of another language.
-
E.
wereInfluencedBy
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
- F. None of above. chosen
Provenance (4 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_69e25d22eb488190914b193aff952e83 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cadf91948190bed71376e6639294 |
completed | April 29, 2026, 9:09 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 8:12 p.m.