Triple
T37378578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .308 Winchester |
E928362
|
entity |
| Predicate | effectiveRangeCategory |
P133442
|
FINISHED |
| Object | medium range |
—
|
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: medium range | Statement: [.308 Winchester, effectiveRangeCategory, medium range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectiveRangeCategory Context triple: [.308 Winchester, effectiveRangeCategory, medium range]
-
A.
hasFiringRange
Indicates that one entity possesses or provides a designated area or capability for discharging weapons over a specified distance.
-
B.
abilityRange
Indicates the spatial or contextual extent within which an entity’s ability, power, or effect can be applied or is valid.
-
C.
isLongRange
Indicates that the relationship or action involves operating effectively over a large or extended distance.
-
D.
hasRangeCategory
chosen
Indicates that a property or measurement falls within a specified category or interval of possible values.
-
E.
operationalRange
Indicates the span of conditions (such as distance, time, or environment) within which a system, device, or process can function effectively and safely.
- 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_69f76eb9e66881908534cf22d04c3b5a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: May 3, 2026, 4:16 p.m.