Triple
T17356027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M1905 bayonet |
E421936
|
entity |
| Predicate | shortenedToBladeLength |
P80659
|
FINISHED |
| Object | 10 inches (for M1 bayonet conversion) |
—
|
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: 10 inches (for M1 bayonet conversion) | Statement: [M1905 bayonet, shortenedToBladeLength, 10 inches (for M1 bayonet conversion)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shortenedToBladeLength Context triple: [M1905 bayonet, shortenedToBladeLength, 10 inches (for M1 bayonet conversion)]
-
A.
wasShortened
chosen
Indicates that something has been made shorter in length, duration, or extent compared to its original form.
-
B.
isShort
Indicates that one entity has a relatively small height, length, or duration compared to a standard or to other entities.
-
C.
weaponLength
Indicates the length or size of a weapon associated with an entity.
-
D.
bladeType
Indicates the specific kind or category of blade associated with an object or entity.
-
E.
hasLowerBarLength
Indicates that one entity’s bar length is shorter than the bar length of another entity.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a487bd8819081c6d1e4aa466d6f |
completed | April 19, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.