Triple
T10984736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L3/35 tankette |
E259598
|
entity |
| Predicate | notableWeakness |
P47330
|
FINISHED |
| Object | thin armor |
—
|
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: thin armor | Statement: [L3/35 tankette, notableWeakness, thin armor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableWeakness Context triple: [L3/35 tankette, notableWeakness, thin armor]
-
A.
hasWeakness
chosen
Indicates that one entity is vulnerable to, or can be adversely affected or defeated by, another entity.
-
B.
hasNotableStrengthIn
Indicates that an entity possesses a particularly high level of ability, effectiveness, or advantage in a specific area or domain.
-
C.
notableSafety
Indicates that an entity is recognized for having significant safety characteristics, performance, or impact relative to others.
-
D.
notableAttack
Indicates that an entity carried out, was involved in, or is strongly associated with a particularly significant or well-known attack.
-
E.
notableProtectiveFailure
Indicates a relationship where an entity’s protective role or safeguards significantly failed, leading to a notable or consequential breakdown in protection.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d772ed1eb88190b7333b746f76a088 |
completed | April 9, 2026, 9:35 a.m. |
| PD | Predicate disambiguation | batch_69d72e9055908190b438f039574aaaaf |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.