Triple
T2651539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Layer Cake |
E53909
|
entity |
| Predicate | basedOnWorkAuthor |
P2806
|
FINISHED |
| Object | J. J. Connolly |
E285872
|
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: J. J. Connolly | Statement: [Layer Cake, basedOnWorkAuthor, J. J. Connolly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: J. J. Connolly Context triple: [Layer Cake, basedOnWorkAuthor, J. J. Connolly]
-
A.
J. J. Connolly
chosen
J. J. Connolly is a British author and screenwriter best known for his crime novel "Layer Cake" and its film adaptation.
-
B.
Mark O’Connor
Mark O’Connor is an American violinist, composer, and fiddler renowned for blending classical, jazz, and American folk traditions, particularly in contemporary string music.
-
C.
Christian O'Connell
Christian O'Connell is a British radio DJ, comedian, and author best known for hosting popular breakfast shows in the UK and Australia.
-
D.
Marc Connelly
Marc Connelly was an American playwright, director, and member of the Algonquin Round Table who won the Pulitzer Prize for Drama for "The Green Pastures."
-
E.
Andrew McElfresh
Andrew McElfresh is an American comedy writer and screenwriter known for his work on films such as "White Chicks."
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd93071248190820197936e3167f7 |
completed | March 7, 2026, 7:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afa052c91c8190abfd49dbc62a4448 |
completed | March 10, 2026, 4:38 a.m. |
Created at: March 6, 2026, 9:53 p.m.