Triple
T16750791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauser C96 |
E407069
|
entity |
| Predicate | chamberedIn |
P9006
|
FINISHED |
| Object | 7.63×25mm Mauser |
—
|
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: 7.63×25mm Mauser | Statement: [Mauser C96, chamberedIn, 7.63×25mm Mauser]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chamberedIn Context triple: [Mauser C96, chamberedIn, 7.63×25mm Mauser]
-
A.
chamberedFor
chosen
Indicates that a firearm is designed or configured to safely accept and fire a specific cartridge or ammunition type in its chamber.
-
B.
chamber1
Indicates that an entity is a chamber or room, typically serving as an enclosed space within a larger structure.
-
C.
chamber2
Indicates that one entity serves as a secondary or inner chamber, room, or compartment associated with another entity.
-
D.
chamberType
Indicates the specific kind or category of chamber associated with an entity (e.g., room, compartment, or enclosed space type).
-
E.
typeOfChamber
Indicates the specific kind or category of chamber that an entity belongs to or is classified as.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa271de48190b4a535408aeef734 |
completed | April 18, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69e319cbd79c8190a03587a61c18bec0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:21 a.m.