Triple
T7684691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Springfield Model 1861 rifle-musket |
E174084
|
entity |
| Predicate | mountsBayonet |
P37995
|
FINISHED |
| Object | socket bayonet |
—
|
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: socket bayonet | Statement: [Springfield Model 1861 rifle-musket, mountsBayonet, socket bayonet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mountsBayonet Context triple: [Springfield Model 1861 rifle-musket, mountsBayonet, socket bayonet]
-
A.
bayonetMount
chosen
Indicates that one object is equipped with or designed to accept a bayonet-style mounting connection to another object.
-
B.
weaponMount
Indicates that one entity serves as a mounting point or support structure for attaching or holding a weapon on another entity.
-
C.
typeOfGunMount
Indicates the specific kind or configuration of gun mounting used to support or attach a gun.
-
D.
sightMounting
Indicates that an entity is equipped with or has a sighting device installed or mounted onto it.
-
E.
missionEquipment
Indicates that certain equipment is assigned to, used for, or associated with carrying out a specific mission.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7048b0b448190889bd40e0a38e51a |
completed | March 27, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69c701618d3481908be84b76f36ac5a1 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4:02 p.m.