Triple
T38184183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John H. Casper |
E1005260
|
entity |
| Predicate | serviceNumberOfCombatMissions |
P7449
|
FINISHED |
| Object | over 200 combat missions in Southeast Asia |
—
|
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: over 200 combat missions in Southeast Asia | Statement: [John H. Casper, serviceNumberOfCombatMissions, over 200 combat missions in Southeast Asia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceNumberOfCombatMissions Context triple: [John H. Casper, serviceNumberOfCombatMissions, over 200 combat missions in Southeast Asia]
-
A.
numberOfMissions
chosen
Indicates the total count of missions associated with a given entity or context.
-
B.
numberOfSuccessfulMissions
Indicates the count of missions that have been completed successfully by the referenced entity or within the specified context.
-
C.
numberLaunchedInCombat
Indicates the quantity of times an entity has been launched or deployed specifically in combat operations.
-
D.
hasFlownSorties
Indicates that an entity has completed one or more operational flight missions (sorties).
-
E.
sawCombatAgainst
Indicates that one entity directly engaged in combat or battle against 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_69f76dbc22c481908139b694ffde7a0c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fdb31800508190beec15adb9bbd292 |
completed | May 8, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69fdb19c381c8190bafb2f565da097f1 |
completed | May 8, 2026, 9:49 a.m. |
Created at: May 3, 2026, 4:29 p.m.