Triple
T10768473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SVT24 |
E254013
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | SVT channels |
E251086
|
NE 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: SVT channels | Statement: [SVT24, partOf, SVT channels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SVT channels Context triple: [SVT24, partOf, SVT channels]
-
A.
SVT
SVT (Special Vehicle Team) is Ford Motor Company's high-performance division responsible for developing enhanced, limited-production models like the Cobra R.
-
B.
SVT
chosen
SVT is Sweden's national public television broadcaster, known for providing news, entertainment, and cultural programming.
-
C.
SVT1
SVT1 is a major Swedish public television channel known for news, current affairs, and a broad range of general-interest programming.
-
D.
Svt
Svt is the station code for Strandvliet, a metro station in Amsterdam, Netherlands.
-
E.
SVT2
SVT2 is a Swedish public television channel known for its focus on culture, current affairs, and minority-language programming.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d7322f9968819098b0ad54b913bfe4 |
completed | April 9, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de236d0a78819090774656b7b492e5 |
completed | April 14, 2026, 11:22 a.m. |
Created at: April 8, 2026, 9:16 p.m.