Triple
T1793175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atari deep Q-network |
E39543
|
entity |
| Predicate | inputFrameStack |
P31980
|
FINISHED |
| Object | 4 consecutive frames |
—
|
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: 4 consecutive frames | Statement: [Atari deep Q-network, inputFrameStack, 4 consecutive frames]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inputFrameStack Context triple: [Atari deep Q-network, inputFrameStack, 4 consecutive frames]
-
A.
usedReferenceFrame
Indicates that one entity adopts or relies on another entity as the coordinate system or reference frame for describing positions, motions, or measurements.
-
B.
frameDevice
Indicates that one entity serves as a structural or supporting frame for another device or object.
-
C.
frameDependent
Indicates that the truth or interpretation of the relationship depends on the particular reference frame, context, or perspective from which it is evaluated.
-
D.
originalFrameRate
Indicates the frame rate at which the original media content was captured or encoded before any conversion or processing.
-
E.
frameType
Indicates the specific structural or categorical kind of frame associated with an entity or relation.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab61b6ea188190aab9fb839bf1e367 |
completed | March 6, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69aa61d2f7a8819090301f92d3e358c7 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab61b5c8988190bb2b46182a4eb5b4 |
completed | March 6, 2026, 11:22 p.m. |
Created at: March 4, 2026, 7:32 p.m.