Triple
T11567870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Sissons |
E274301
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Channel 4 News |
E68543
|
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: Channel 4 News | Statement: [Peter Sissons, notableWork, Channel 4 News]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Channel 4 News Context triple: [Peter Sissons, notableWork, Channel 4 News]
-
A.
Channel 4
chosen
Channel 4 is a British public-service television broadcaster known for its innovative, often provocative programming and support of diverse and groundbreaking drama and comedy.
-
B.
Channel 4
Channel 4 is the on-air brand used by Pittsburgh television station WTAE-TV, an ABC-affiliated local broadcast outlet.
-
C.
BBC News Channel
BBC News Channel is a 24-hour British television news service providing rolling national and international news coverage.
-
D.
Sky News
Sky News is a British 24-hour television news channel and digital news service known for live breaking news coverage in the UK and internationally.
-
E.
Channel 4 News Team
The Channel 4 News Team is the fictional San Diego television news crew featured in the comedy film "Anchorman: The Legend of Ron Burgundy."
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd4305c8190ac5ff490b6b63e12 |
completed | April 10, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e713bcc0048190bec14ac4ab84d51d |
completed | April 21, 2026, 6:05 a.m. |
Created at: April 8, 2026, 9:37 p.m.