Triple
T9019072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Balikpapan (1945) |
E215666
|
entity |
| Predicate | involvedAirSupport |
P23972
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Battle of Balikpapan (1945), involvedAirSupport, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedAirSupport Context triple: [Battle of Balikpapan (1945), involvedAirSupport, yes]
-
A.
involvedAirborneOperations
Indicates that an entity participated in or conducted military operations involving the use of aircraft to deploy or support forces.
-
B.
airForceInvolved
chosen
Indicates that an air force participates in, contributes to, or is otherwise involved in a specified event, operation, or situation.
-
C.
airborneForces
Indicates that military forces are deployed, transported, or operating via aircraft, typically inserted from the air into an operational area.
-
D.
supportsMedEvacOperations
Indicates the capability or role of providing assistance, resources, or infrastructure necessary to conduct medical evacuation operations.
-
E.
airliftOrganizedBy
Indicates that an airlift operation is planned, coordinated, or managed by a specified organizing 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_69ca83a38aa88190bf1bb80c4548b5e2 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a4085848190a6aa440e6307e93d |
completed | April 1, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:07 p.m.