Triple
T22297242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grumman F9F Panther |
E551151
|
entity |
| Predicate | armamentStores |
P147968
|
FINISHED |
| Object | underwing bombs |
—
|
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: underwing bombs | Statement: [Grumman F9F Panther, armamentStores, underwing bombs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentStores Context triple: [Grumman F9F Panther, armamentStores, underwing bombs]
-
A.
armamentStations
Indicates a relationship where specific locations or mounts on a platform (such as a vehicle, vessel, or structure) are designated for installing or carrying weapons or armaments.
-
B.
armory
Indicates that an entity serves as a place where weapons, armor, or military equipment are stored, maintained, or supplied for use.
-
C.
armsTrade
Indicates the buying, selling, or exchange of weapons or military equipment between parties.
-
D.
armamentCount
Indicates the number of weapons or armaments associated with an entity.
-
E.
armamentCategory
Indicates the classification of a weapon or military equipment according to its type or role in armament systems.
- 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15720fba0819080f6c96f6df4f1e0 |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e72ffa438481908f80879aef2a589b |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e75dc7b08081909d64441e979c2fa4 |
completed | April 21, 2026, 11:21 a.m. |
Created at: April 16, 2026, 8:41 p.m.