Triple
T31815983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TAM VCLC |
E812133
|
entity |
| Predicate | armoredProtectionLevel |
P82099
|
FINISHED |
| Object | similar to TAM tank hull |
—
|
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: similar to TAM tank hull | Statement: [TAM VCLC, armoredProtectionLevel, similar to TAM tank hull]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armoredProtectionLevel Context triple: [TAM VCLC, armoredProtectionLevel, similar to TAM tank hull]
-
A.
armorProtectionLevel
chosen
Indicates the degree or rating of protective capability that armor provides against threats or damage.
-
B.
armourProtection
Indicates that one entity provides protective armor or defensive covering for another entity.
-
C.
armourThickness
Indicates the measured thickness of an entity’s protective armor in the context of defense or shielding.
-
D.
hasArmorPlating
Indicates that one entity is equipped with or covered by protective armor plating in relation to another entity or context.
-
E.
armoredBeltThickness
Indicates the thickness of an entity’s protective armored belt in the context of its defensive structure or design.
- 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_69f348e846c081908eb468a0665afd55 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca3dedc81908b519d53d2909868 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 30, 2026, 11:44 p.m.