Triple
T5609734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Marianas Turkey Shoot |
E147321
|
entity |
| Predicate | JapaneseAircraftLosses |
P684
|
FINISHED |
| Object | more than 200 carrier aircraft destroyed in air combat |
—
|
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: more than 200 carrier aircraft destroyed in air combat | Statement: [Great Marianas Turkey Shoot, JapaneseAircraftLosses, more than 200 carrier aircraft destroyed in air combat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JapaneseAircraftLosses Context triple: [Great Marianas Turkey Shoot, JapaneseAircraftLosses, more than 200 carrier aircraft destroyed in air combat]
-
A.
aircraftLostByJapan
chosen
Indicates that the specified aircraft were lost by Japan, typically through destruction, damage beyond repair, or disappearance.
-
B.
aircraftLosses
Indicates the number or occurrence of aircraft that have been destroyed, damaged beyond repair, or otherwise lost.
-
C.
casualtiesJapan
Indicates that an event or action resulted in casualties (deaths and/or injuries) occurring in Japan.
-
D.
JapaneseAirCommander
Indicates that one entity serves as a Japanese air force commander in relation to another entity or context.
-
E.
aircraftDestroyedUS
Indicates that a U.S. aircraft has been destroyed.
- 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0211dfc88819097b6d4254a61f65a |
completed | March 22, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.