Triple
T19937024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CNN International |
E479198
|
entity |
| Predicate | sisterChannel |
P5818
|
FINISHED |
| Object | CNN Türk |
—
|
NE NERFINISHED |
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: CNN Türk | Statement: [CNN International, sisterChannel, CNN Türk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CNN Türk Context triple: [CNN International, sisterChannel, CNN Türk]
-
A.
CNN Türk
chosen
CNN Türk is a major Turkish television news channel that provides 24-hour national and international news coverage.
-
B.
Turkish Radio and Television Corporation
The Turkish Radio and Television Corporation is Turkey’s national public broadcaster, operating multiple television and radio channels domestically and internationally.
-
C.
TRT Haber
TRT Haber is a Turkish public television news channel providing national and international news coverage as part of the state broadcaster TRT.
-
D.
Kanal D
Kanal D is a major Turkish television channel known for broadcasting popular series, entertainment programs, and news.
-
E.
Acun Medya
Acun Medya is a Turkish media production company founded by television producer and presenter Acun Ilıcalı, best known for creating and adapting popular reality and entertainment shows.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a17fb2c8190b3aaae88e741648a |
completed | April 20, 2026, 4:53 p.m. |
Created at: April 10, 2026, 1:53 p.m.