Triple
T1239887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urgent Fury |
E26633
|
entity |
| Predicate | CubanCasualtiesWounded |
P25871
|
FINISHED |
| Object | 59 |
—
|
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: 59 | Statement: [Urgent Fury, CubanCasualtiesWounded, 59]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CubanCasualtiesWounded Context triple: [Urgent Fury, CubanCasualtiesWounded, 59]
-
A.
casualtiesGrenadianAndCuban
Indicates that the relationship involves casualties suffered by both Grenadian and Cuban parties in a given event or context.
-
B.
casualtiesWoundedUS
Indicates that the relationship specifies the number of U.S. individuals who were wounded as casualties in an event or incident.
-
C.
CubanLeaderInvolved
Indicates that a Cuban leader is directly involved in, associated with, or plays a significant role in a specified event, action, or relationship.
-
D.
casualtiesEstimate
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
-
E.
casualtiesBritishWounded
Indicates the number of British individuals who were wounded as a result of a specific event or action.
- 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf41c5d08190b07adbdb24d35a76 |
completed | March 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69a4bb696a38819095845c84f0241287 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bce611ec819092cb13d354d0903e |
completed | March 1, 2026, 10:25 p.m. |
Created at: March 1, 2026, 7:47 p.m.