Triple
T18884938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karan Thapar |
E461933
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object |
CNN-IBN
CNN-IBN is an Indian English-language news television channel (now known as CNN-News18) recognized for its national and international news coverage and current affairs programming.
|
E1348539
|
NE FINISHED |
How this triple was built (4 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-IBN | Statement: [Karan Thapar, employer, CNN-IBN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CNN-IBN Context triple: [Karan Thapar, employer, CNN-IBN]
-
A.
CNN2
CNN2 was the original name of HLN, a U.S. cable news channel that focused on headline news and brief, continuously updated reports.
-
B.
CNews
CNews is a French 24-hour television news channel known for its rolling news coverage and opinion-led programming.
-
C.
Sansad TV
Sansad TV is an Indian parliamentary television channel that provides live coverage and analysis of proceedings from the country's legislative bodies along with related public affairs programming.
-
D.
CNN
CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
-
E.
NDTV
NDTV is a prominent Indian news media company best known for its nationwide television news channels and digital journalism platforms.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: CNN-IBN Triple: [Karan Thapar, employer, CNN-IBN]
Generated description
CNN-IBN is an Indian English-language news television channel (now known as CNN-News18) recognized for its national and international news coverage and current affairs programming.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CNN-IBN Target entity description: CNN-IBN is an Indian English-language news television channel (now known as CNN-News18) recognized for its national and international news coverage and current affairs programming.
-
A.
CNN2
CNN2 was the original name of HLN, a U.S. cable news channel that focused on headline news and brief, continuously updated reports.
-
B.
CNews
CNews is a French 24-hour television news channel known for its rolling news coverage and opinion-led programming.
-
C.
Sansad TV
Sansad TV is an Indian parliamentary television channel that provides live coverage and analysis of proceedings from the country's legislative bodies along with related public affairs programming.
-
D.
CNN
CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
-
E.
NDTV
NDTV is a prominent Indian news media company best known for its nationwide television news channels and digital journalism platforms.
- F. None of above. chosen
Provenance (5 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d53e608190b8740c092b6e1523 |
completed | April 20, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0582b19ea081909438a6c7ba75316d |
completed | May 14, 2026, 8:07 a.m. |
| NEDg | Description generation | batch_6a0589d4f0448190a054bf1beb1607c7 |
completed | May 14, 2026, 8:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a058a7e4604819094e32ed3a6aeda47 |
completed | May 14, 2026, 8:40 a.m. |
Created at: April 10, 2026, 11:57 a.m.