Triple
T35568728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Orleans-class cruiser |
E1027850
|
entity |
| Predicate | sawExtensiveServiceDuring |
P86722
|
FINISHED |
| Object | World War II |
—
|
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: World War II | Statement: [New Orleans-class cruiser, sawExtensiveServiceDuring, World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sawExtensiveServiceDuring Context triple: [New Orleans-class cruiser, sawExtensiveServiceDuring, World War II]
-
A.
sawExtensiveService
chosen
Indicates that the subject was used or employed heavily and over a long period of time, often in an operational or practical capacity.
-
B.
sawServiceDuring
Indicates that one entity experienced or utilized a service during the time period associated with another entity or event.
-
C.
sawServicePeriod
Indicates that one entity observed or was aware of the duration or specific period during which a service was provided or active.
-
D.
serviceDuring
Indicates that one entity performs or provides a service for another entity during a specified time period or event.
-
E.
hasVehicleService
Indicates that one entity provides, performs, or is responsible for vehicle-related services for another entity.
- 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:04 p.m.