Triple
T1056327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HLN |
E22803
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | CNN Worldwide |
E10223
|
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: CNN Worldwide | Statement: [HLN, partOf, CNN Worldwide]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CNN Worldwide Context triple: [HLN, partOf, CNN Worldwide]
-
A.
CNN
chosen
CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
-
B.
Fox News International
Fox News International is the global subscription streaming service that delivers Fox News Channel and related programming to audiences outside the United States.
-
C.
BBC News Channel
BBC News Channel is a 24-hour British television news service providing rolling national and international news coverage.
-
D.
ABC News
ABC News is the news division of the American Broadcasting Company, providing television, digital, and radio news coverage in the United States and internationally.
-
E.
CNBC
CNBC is an American business news television channel known for its real-time financial market coverage and economic analysis.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d9102c819090af78cae50f0ff2 |
completed | March 1, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bd110ac8190b66163de42bd3034 |
completed | March 7, 2026, 2:53 p.m. |
Created at: March 1, 2026, 7:42 p.m.