Triple
T27213501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brewster Buffalo |
E684066
|
entity |
| Predicate | sawCombatInRegion |
P162257
|
FINISHED |
| Object | Pacific theater |
—
|
NE NERFINISHED |
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: Pacific theater | Statement: [Brewster Buffalo, sawCombatInRegion, Pacific theater]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sawCombatInRegion Context triple: [Brewster Buffalo, sawCombatInRegion, Pacific theater]
-
A.
sawCombat
Indicates that an entity directly participated in active military or armed conflict.
-
B.
sawCombatant
Indicates that one entity directly observed or witnessed another entity who is engaged as a combatant in a conflict or battle.
-
C.
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.
-
D.
battleParticipated
Indicates that an entity took part in a specific battle as a combatant or participant.
-
E.
didNotSeeCombat
Indicates that the subject did not participate in or experience active combat or battle.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6261ae5488190aaa5d47d94097d12 |
completed | May 2, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f622a8fe7c819096e8a43db263a423 |
completed | May 2, 2026, 4:13 p.m. |
Created at: April 27, 2026, 9:40 a.m.