Triple
T4322993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .50 caliber M2 Browning machine gun |
E96562
|
entity |
| Predicate | effectiveRange |
P45893
|
FINISHED |
| Object | approximately 1,800 meters |
—
|
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 1,800 meters | Statement: [.50 caliber M2 Browning machine gun, effectiveRange, approximately 1,800 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectiveRange Context triple: [.50 caliber M2 Browning machine gun, effectiveRange, approximately 1,800 meters]
-
A.
tieneAlcance
chosen
Indicates that something possesses or has a certain scope, reach, or range of effect in relation to something else.
-
B.
hasLongerReachThan
Indicates that one entity can extend, influence, or physically reach farther than another entity.
-
C.
operationalRange
Indicates the span of conditions (such as distance, time, or environment) within which a system, device, or process can function effectively and safely.
-
D.
frontArmorRange
Indicates the range or extent of protective armor coverage on the front-facing side of an entity.
-
E.
gunElevationRange
Indicates the range of vertical angles through which a gun can be elevated or depressed relative to a reference plane.
- 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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351177eb88190b89fa49a88add5e8 |
completed | March 12, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69b34f4bec888190987fc2631498b637 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:12 p.m.