Triple
T15381642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daphne Clunes |
E367817
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Daphne Clunes |
E367817
|
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: Daphne Clunes | Statement: [Daphne Clunes, name, Daphne Clunes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daphne Clunes Context triple: [Daphne Clunes, name, Daphne Clunes]
-
A.
Daphne Clunes
chosen
Daphne Clunes is the daughter of English actor Martin Clunes.
-
B.
Emily Clunes
Emily Clunes is the daughter of English actor and comedian Martin Clunes.
-
C.
Alison Steadman
Alison Steadman is an acclaimed English actress known for her versatile work in television, film, and theatre, including notable roles in Mike Leigh collaborations and classic literary adaptations.
-
D.
Fern Britton
Fern Britton is a British television presenter and author best known for her long-running work on daytime TV and her warm, approachable on-screen style.
-
E.
Lara Bingle
Lara Bingle is an Australian model, media personality, and entrepreneur best known for her high-profile advertising campaigns and reality television appearances.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e61928c81908852c355d537ed9c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a6b67c08190b0df6b9fd65ff28b |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:19 a.m.