Triple
T10588103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Andrew Marr Show |
E249907
|
entity |
| Predicate | presenter |
P83
|
FINISHED |
| Object | Andrew Marr |
E50189
|
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: Andrew Marr | Statement: [The Andrew Marr Show, presenter, Andrew Marr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Marr Context triple: [The Andrew Marr Show, presenter, Andrew Marr]
-
A.
Andrew Marr
chosen
Andrew Marr is a prominent British journalist, broadcaster, and political commentator best known for presenting BBC current affairs programmes such as "The Andrew Marr Show."
-
B.
James Marr
James Marr is a relatively obscure individual whose primary distinction is sharing the surname associated with the better-known Marr family name.
-
C.
Jeremy Paxman
Jeremy Paxman is a British broadcaster, journalist, and author best known for his incisive interviewing style on BBC’s Newsnight and as the long-time host of the quiz show University Challenge.
-
D.
Lem Dobbs
Lem Dobbs is a British-American screenwriter known for his work on films such as "Dark City," "The Limey," and "The Score."
-
E.
Andrew Neil
Andrew Neil is a veteran British journalist and broadcaster known for his incisive political interviews and leadership roles at major UK media outlets.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d527793c588190bfe3a5261eb7f919 |
completed | April 7, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a1bba1c8190af5a078f40f3bc0a |
completed | April 10, 2026, 10:30 p.m. |
Created at: April 6, 2026, 12:40 p.m.