Triple
T722410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PT-91 Twardy |
E14645
|
entity |
| Predicate | hasNightVision |
P18629
|
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: [PT-91 Twardy, hasNightVision, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNightVision Context triple: [PT-91 Twardy, hasNightVision, yes]
-
A.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
B.
hasPerception
Indicates that one entity is aware of, senses, or recognizes another entity or phenomenon.
-
C.
hasTorchRelay
Indicates that an event or entity includes or is associated with a torch relay as part of its activities or proceedings.
-
D.
containsVisionOf
Indicates that one entity includes, depicts, or embodies a visual representation or image of another entity.
-
E.
capturedEquipment
Indicates that one party has taken possession of another party’s equipment, typically as a result of conflict, competition, or enforcement.
- F. None of above. chosen
Provenance (4 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a591124c8190842e7ef18b064198 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f700cc81908c6de3eedf68433c |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a55a26e081908134ee93faaf7c40 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.