Triple
T32852716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl Gustaf M3 |
E840296
|
entity |
| Predicate | antiArmorEffectiveRange |
P152572
|
FINISHED |
| Object | approximately 500 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 500 meters | Statement: [Carl Gustaf M3, antiArmorEffectiveRange, approximately 500 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antiArmorEffectiveRange Context triple: [Carl Gustaf M3, antiArmorEffectiveRange, approximately 500 meters]
-
A.
frontArmorRange
Indicates the range or extent of protective armor coverage on the front-facing side of an entity.
-
B.
effectivenessAgainst
Indicates how well one entity performs in countering, influencing, or mitigating the impact of another entity.
-
C.
hasFiringRange
chosen
Indicates that one entity possesses or provides a designated area or capability for discharging weapons over a specified distance.
-
D.
armorProtectionLevel
Indicates the degree or rating of protective capability that armor provides against threats or damage.
-
E.
NKArmorStrength
Indicates the degree of protective strength or durability provided by a piece of armor.
- 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_69f349412c78819084459850e11d29f7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6ce7a02488190a1dd08ed8e97512d |
completed | May 3, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:17 a.m.