Triple
T7444881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Springfield Model 1795 musket |
E171851
|
entity |
| Predicate | hasBayonet |
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 1795 musket, hasBayonet, socket bayonet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBayonet Context triple: [Springfield Model 1795 musket, hasBayonet, 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.
hasBowType
Indicates that an entity possesses or is associated with a specific type or category of bow.
-
C.
armedBy
Indicates that one entity is supplied with weapons, equipment, or armaments by another entity.
-
D.
hasWeaponType
Indicates that an entity is associated with or equipped with a specific type or category of weapon.
-
E.
usedWeapon
Indicates that an entity employed a specific weapon as the means or tool to carry out an action or event.
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f37054388190a6cb4c0db2ca6014 |
completed | March 27, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c6f039f7248190bb4183f97b605763 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:14 p.m.