Triple
T20460092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TR-85M1 Bizonul |
E501900
|
entity |
| Predicate | hasFireSuppressionSystem |
P127083
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [TR-85M1 Bizonul, hasFireSuppressionSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFireSuppressionSystem Context triple: [TR-85M1 Bizonul, hasFireSuppressionSystem, yes]
-
A.
hasFireExtinguishers
chosen
Indicates that the subject is equipped with or possesses one or more fire extinguishers.
-
B.
hasSprinklers
Indicates that an entity is equipped with or contains sprinkler systems.
-
C.
hasFireControlSystem
Indicates that an entity is equipped with or includes a fire control system used to detect, track, and direct weapons or suppression against targets.
-
D.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
-
E.
hasVacuumSystem
Indicates that one entity is equipped with, or includes as a component, a vacuum system.
- 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a549a48190a1bcd7a6b0f71a11 |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.