Triple
T27213515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brewster Buffalo |
E684066
|
entity |
| Predicate | sawCombatAgainst |
P162632
|
FINISHED |
| Object | Imperial Japanese Army Air Force aircraft |
—
|
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: Imperial Japanese Army Air Force aircraft | Statement: [Brewster Buffalo, sawCombatAgainst, Imperial Japanese Army Air Force aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sawCombatAgainst Context triple: [Brewster Buffalo, sawCombatAgainst, Imperial Japanese Army Air Force aircraft]
-
A.
sawCombatAgainst
chosen
Indicates that one entity directly engaged in combat or battle against another entity.
-
B.
sawCombat
Indicates that an entity directly participated in active military or armed conflict.
-
C.
sawCombatant
Indicates that one entity directly observed or witnessed another entity who is engaged as a combatant in a conflict or battle.
-
D.
sawCombatInRegion
Indicates that an entity participated in combat operations within a specified geographic region.
-
E.
battledIn
Indicates that two or more entities engaged in a battle or conflict that took place at a specific location or during a particular event.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 9:40 a.m.