Triple
T19449200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Gwillim |
E486566
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | David Gwillim |
—
|
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: David Gwillim | Statement: [David Gwillim, name, David Gwillim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Gwillim Context triple: [David Gwillim, name, David Gwillim]
-
A.
David Gwillim
chosen
David Gwillim is a British actor known for his work in television and film, particularly in period dramas and literary adaptations.
-
B.
David Larkham
David Larkham is a British graphic artist and illustrator best known for his extensive album cover and design work for Elton John in the 1970s.
-
C.
Graham Waterston
Graham Waterston is an American filmmaker and the son of acclaimed actor Sam Waterston.
-
D.
Gareth H. McKinley
Gareth H. McKinley is a prominent mechanical engineer and rheologist known for his influential research on complex fluids and non-Newtonian flow behavior.
-
E.
Graham Dumpleton
Graham Dumpleton is a software engineer and open-source developer best known for creating and maintaining mod_wsgi, a popular Apache module for hosting Python web applications.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338be5a48190973d9ecae853900c |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.