Triple
T36739879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smith & Wesson Model 10 |
E907578
|
entity |
| Predicate | typicalWeightUnloaded |
P18770
|
FINISHED |
| Object | approximately 34 ounces (4-inch barrel version) |
—
|
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: approximately 34 ounces (4-inch barrel version) | Statement: [Smith & Wesson Model 10, typicalWeightUnloaded, approximately 34 ounces (4-inch barrel version)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWeightUnloaded Context triple: [Smith & Wesson Model 10, typicalWeightUnloaded, approximately 34 ounces (4-inch barrel version)]
-
A.
emptyWeight
chosen
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
-
B.
typicalCarWeight
Indicates the usual or characteristic weight associated with a given car.
-
C.
carriageWeight
Indicates the weight or mass associated with a carriage in the described context.
-
D.
weightLimitInKilograms
Indicates the maximum allowable weight for something, expressed in kilograms.
-
E.
weightLimitInPounds
Indicates the maximum allowable weight for something, expressed in pounds.
- 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_69f76e75aa6881909b844d00a3888ee5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:12 p.m.