Triple
T13170941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .30 cal Browning M1919A4 machine guns |
E312971
|
entity |
| Predicate | caseEjection |
P49676
|
FINISHED |
| Object | bottom ejection |
—
|
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: bottom ejection | Statement: [.30 cal Browning M1919A4 machine guns, caseEjection, bottom ejection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseEjection Context triple: [.30 cal Browning M1919A4 machine guns, caseEjection, bottom ejection]
-
A.
canEject
Indicates that one entity has the ability or permission to forcibly remove or expel another entity from a place, system, or context.
-
B.
hasEjecta
chosen
Indicates that one entity produces or is associated with material expelled or thrown out from another entity as a result of an energetic event or process.
-
C.
hasEjectionSeat
Indicates that an object (typically a vehicle or cockpit) is equipped with an ejection seat that allows an occupant to be forcibly expelled for emergency escape.
-
D.
castOutOf
Indicates that one entity is expelled or forcibly removed from another entity, place, or group.
-
E.
involvesParticleEjection
Indicates that the action or process includes the emission or release of particles from a source.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc2c0c88190be357811aa8e828d |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:13 p.m.