Triple
T37578018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | beIN SERIES |
E934876
|
entity |
| Predicate | usesPictureFormat |
P109452
|
FINISHED |
| Object | HDTV 1080i |
—
|
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: HDTV 1080i | Statement: [beIN SERIES, usesPictureFormat, HDTV 1080i]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPictureFormat Context triple: [beIN SERIES, usesPictureFormat, HDTV 1080i]
-
A.
typicalPictureFormat
Indicates the standard or most commonly used picture format associated with an entity (such as a device, medium, or context).
-
B.
formerPictureFormat
Indicates that an entity previously used a particular picture format before changing to a different one.
-
C.
usesFilmFormat
Indicates that one entity employs or is recorded in a particular film format associated with the other entity.
-
D.
supportsJPEG
Indicates that one entity is capable of handling, displaying, or processing JPEG image files for another entity or in a given context.
-
E.
usedFormat
chosen
Indicates that one entity employs or applies a particular format or representation in relation to 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_69f76ecd99148190be327e391a70f5b6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: May 3, 2026, 4:17 p.m.