Triple
T30555825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shimushiru |
E777693
|
entity |
| Predicate | countryHistoricallyUsingName |
P138136
|
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: [Shimushiru, countryHistoricallyUsingName, Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryHistoricallyUsingName Context triple: [Shimushiru, countryHistoricallyUsingName, Japan]
-
A.
countryInThePast
Indicates that an entity was recognized as a country during some period in the past, but is not necessarily a country in the present.
-
B.
historicallyAssociatedWithModernCountry
chosen
Indicates that an entity has a significant historical connection, influence, or origin related to a specified modern country.
-
C.
countryOfHistoricRole
Indicates the country in which an entity held a significant historical role or carried out historically notable activities.
-
D.
politicalEntityHistorically
Indicates that a political entity held a particular status, role, or relationship during a past historical period, but not necessarily in the present.
-
E.
countryAtTheTime
Indicates that an entity is associated with a specific country as it existed at a particular point in time.
- 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_69f2249e19108190a458ab446096bf22 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff84df768c81908c65a1a7e33103ad |
completed | May 9, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69ff848d0af881908ee42c27a58af47e |
completed | May 9, 2026, 7:01 p.m. |
Created at: April 29, 2026, 8:20 p.m.