Triple
T20262742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julian Barnes |
E498884
|
entity |
| Predicate | hasPseudonym |
P3799
|
FINISHED |
| Object | Dan Kavanagh |
—
|
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 Kavanagh | Statement: [Julian Barnes, hasPseudonym, Dan Kavanagh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Kavanagh Context triple: [Julian Barnes, hasPseudonym, Dan Kavanagh]
-
A.
Dan Kavanagh
chosen
Dan Kavanagh is the crime-fiction pseudonym used by British novelist Julian Barnes for a series of detective novels.
-
B.
Brian Kavanagh
Brian Kavanagh is a film editor best known for his work on notable Australian and international films, including the drama "The Devil's Playground."
-
C.
Luke Doolan
Luke Doolan is an Australian film editor and filmmaker best known for his work on acclaimed films such as "Animal Kingdom."
-
D.
Andy Loughnane
Andy Loughnane is a sports business executive known for leading the front-office and business operations of Major League Soccer club Austin FC.
-
E.
Brian Callaghan
Brian Callaghan is a personal name shared by multiple individuals, typically of Irish or British origin, who may be notable in various professional or public contexts.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674cba2748190a886ecd8316dc518 |
completed | April 20, 2026, 6:47 p.m. |
Created at: April 11, 2026, 11:41 p.m.