Triple
T1793174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atari deep Q-network |
E39543
|
entity |
| Predicate | inputFrameSize |
P31979
|
FINISHED |
| Object | 84x84 grayscale images |
—
|
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: 84x84 grayscale images | Statement: [Atari deep Q-network, inputFrameSize, 84x84 grayscale images]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inputFrameSize Context triple: [Atari deep Q-network, inputFrameSize, 84x84 grayscale images]
-
A.
minimumFrameSize
Indicates the smallest allowable or supported size of a frame in the given context or system.
-
B.
originalFrameRate
Indicates the frame rate at which the original media content was captured or encoded before any conversion or processing.
-
C.
packetSize
Indicates the size or amount of data contained in a packet within a communication or data transfer context.
-
D.
blockSize
Indicates the size or capacity of a discrete block unit within a larger structure or system.
-
E.
fieldSize
Indicates the magnitude or dimensions of a field associated with an entity or context.
- 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.