Triple
T16244254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dane DeHaan |
E394328
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Daniel Radcliffe |
E95151
|
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: Daniel Radcliffe | Statement: [Dane DeHaan, workedWith, Daniel Radcliffe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Radcliffe Context triple: [Dane DeHaan, workedWith, Daniel Radcliffe]
-
A.
Daniel Radcliffe
chosen
Daniel Radcliffe is an English actor best known for playing the title role in the Harry Potter film series.
-
B.
Rupert Grint
Rupert Grint is an English actor best known for playing Ron Weasley in the Harry Potter film series.
-
C.
James Norton
James Norton is a British actor known for his roles in television series such as "Grantchester," "Happy Valley," and "McMafia," as well as various film and stage productions.
-
D.
Harry Melling
Harry Melling is an English actor known for his role as Dudley Dursley in the Harry Potter film series and for his later work in film and television, including acclaimed character performances in period dramas and thrillers.
-
E.
JasonBiggs
JasonBiggs is an American actor best known for his role as Jim Levenstein in the "American Pie" film series.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24560c6848190ae0e85ecb11a9264 |
completed | April 17, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ee135b881909cc1b6919bc7af29 |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:04 a.m.