Triple
T31582741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VT52 |
E805868
|
entity |
| Predicate | supportsReverseVideo |
P207465
|
FINISHED |
| Object | model-dependent |
—
|
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: model-dependent | Statement: [VT52, supportsReverseVideo, model-dependent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsReverseVideo Context triple: [VT52, supportsReverseVideo, model-dependent]
-
A.
supportsMonochromeMonitor
Indicates that one entity is capable of operating with, driving, or is compatible with a monochrome (single-color) monitor.
-
B.
supportsMoreColorsThan
Indicates that one entity is capable of displaying or handling a greater number of distinct colors than another entity.
-
C.
supportsVerticalVideo
Indicates that one entity provides compatibility with or proper handling of vertical (portrait-oriented) video content for another entity.
-
D.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
E.
supportsColorBurstOnComposite
Indicates that a system or device is capable of maintaining and outputting the color burst signal correctly when generating or processing a composite video signal.
- 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_69f348d3a86c8190a3e5e539a4dd125f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 30, 2026, 10:24 p.m.