Triple
T22387238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Edwina Grosvenor |
E553425
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Dan Snow |
—
|
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: Dan Snow | Statement: [Lady Edwina Grosvenor, spouse, Dan Snow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Snow Context triple: [Lady Edwina Grosvenor, spouse, Dan Snow]
-
A.
Dan Snow
chosen
Dan Snow is a British historian and television presenter known for his documentaries and books on military and world history.
-
B.
Giles Paxman
Giles Paxman is a British former diplomat who served as the United Kingdom's ambassador to Mexico and later to Spain.
-
C.
Andrew Marr
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."
-
D.
Nicholas Collon
Nicholas Collon is a British conductor known for his work with leading European orchestras and for championing contemporary and Nordic repertoire.
-
E.
Iain Morris
Iain Morris is a British writer and director best known for co-creating the hit sitcom "The Inbetweeners."
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158304bcc81908c4c5db09a246bcc |
completed | April 29, 2026, 1 a.m. |
Created at: April 16, 2026, 8:45 p.m.