Triple
T6758223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese cruiser Kinugasa |
E154516
|
entity |
| Predicate | prewarService |
P33336
|
FINISHED |
| Object | training cruises and fleet maneuvers |
—
|
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: training cruises and fleet maneuvers | Statement: [Japanese cruiser Kinugasa, prewarService, training cruises and fleet maneuvers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prewarService Context triple: [Japanese cruiser Kinugasa, prewarService, training cruises and fleet maneuvers]
-
A.
preWarServiceArea
Indicates the geographic area or jurisdiction in which an entity operated or provided service before a specified war or conflict.
-
B.
prewarActivity
chosen
Indicates activities, conditions, or behaviors that occurred or were carried out before a specific war or armed conflict.
-
C.
preWarCharacter
Indicates that a character existed or had a particular state or role prior to a specified war or conflict.
-
D.
preWarCountry
Indicates that a country existed or held a particular status prior to a specified war or major armed conflict.
-
E.
preWarOccupation
Indicates the occupation or role a person held before a specific war or armed conflict.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:11 p.m.