Triple
T4812587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinking of HMS Repulse |
E107105
|
entity |
| Predicate | attackingAircraftOrigin |
P59772
|
FINISHED |
| Object | Japanese airfields in Indochina |
—
|
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: Japanese airfields in Indochina | Statement: [Sinking of HMS Repulse, attackingAircraftOrigin, Japanese airfields in Indochina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attackingAircraftOrigin Context triple: [Sinking of HMS Repulse, attackingAircraftOrigin, Japanese airfields in Indochina]
-
A.
opponentAircraft
Indicates that one aircraft is an adversary or opposing aircraft relative to another in a conflict or competitive context.
-
B.
targetedAircraft
Indicates that one entity has selected or designated an aircraft as the object of an attack, tracking, or other directed action.
-
C.
launchedAircraftIn
Indicates that an entity initiated the takeoff or deployment of an aircraft within a specified location or context.
-
D.
usedAircraftOrigin
Indicates the place or source from which a used aircraft was originally obtained or came.
-
E.
mainFighterAircraft
Indicates that an aircraft serves as the primary fighter aircraft for a given country, organization, or military force.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:23 p.m.