Triple
T18016585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RetinaNet |
E431010
|
entity |
| Predicate | usesAnchorBoxes |
P129423
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [RetinaNet, usesAnchorBoxes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAnchorBoxes Context triple: [RetinaNet, usesAnchorBoxes, true]
-
A.
usesNeuralNetworks
Indicates that one entity employs neural network models or techniques as part of its functioning, processing, or decision-making.
-
B.
usesClassifiers
Indicates that one entity employs or relies on a system of classifiers (such as category labels or measure words) when referring to or organizing another entity.
-
C.
requiresFineTuningOf
Indicates that one entity needs the adjustment, calibration, or refinement of another entity in order to function correctly or optimally.
-
D.
inceptionApproximation
Indicates an approximate or estimated starting point or origin of something, rather than an exact inception time.
-
E.
coAnchorWith
Indicates that two or more people jointly serve as anchors or hosts of the same program, segment, or broadcast.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9be5d0c819097e006f32d98753a |
completed | April 19, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:24 a.m.