Triple
T9030170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMPTE timecode |
E216147
|
entity |
| Predicate | VITCencodedIn |
P1444
|
FINISHED |
| Object | vertical blanking interval of video signal |
—
|
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: vertical blanking interval of video signal | Statement: [SMPTE timecode, VITCencodedIn, vertical blanking interval of video signal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: VITCencodedIn Context triple: [SMPTE timecode, VITCencodedIn, vertical blanking interval of video signal]
-
A.
encodedIn
chosen
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
B.
encodes
Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic form.
-
C.
notEncodedIn
Indicates that a piece of information, data, or content is explicitly absent from or not represented within a given encoding, format, or medium.
-
D.
usesCodec
Indicates that one entity employs or relies on a specific codec to encode, decode, or process data.
-
E.
videoEncoding
Indicates that one entity is used to encode, compress, or transform video data into a particular digital format or representation for another entity.
- F. None of above.
Provenance (3 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a9e0aa881908886f453c51ecd0e |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:08 p.m.