Triple
T21148049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CNN Headline News |
E521112
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | CNN2 |
—
|
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: CNN2 | Statement: [CNN Headline News, formerName, CNN2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CNN2 Context triple: [CNN Headline News, formerName, CNN2]
-
A.
CNN2
chosen
CNN2 was the original name of HLN, a U.S. cable news channel that focused on headline news and brief, continuously updated reports.
-
B.
CNN.com
CNN.com is the online news website of CNN, providing global news coverage, analysis, and multimedia content.
-
C.
CNN
CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
-
D.
CNews
CNews is a French 24-hour television news channel known for its rolling news coverage and opinion-led programming.
-
E.
CNN International
CNN International is a global 24-hour news television channel providing international news coverage and analysis to audiences worldwide.
- 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e723fe9da88190b65c370b1efcbb96 |
completed | April 21, 2026, 7:15 a.m. |
Created at: April 16, 2026, 2:58 p.m.