Triple
T21944286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inferno (2016 film) |
E541895
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Dan Hanley |
—
|
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 Hanley | Statement: [Inferno (2016 film), editedBy, Dan Hanley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Hanley Context triple: [Inferno (2016 film), editedBy, Dan Hanley]
-
A.
Dan Hanley
chosen
Dan Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
-
B.
Brent Hanley
Brent Hanley is an American screenwriter best known for writing the critically acclaimed film "Frailty" (2001).
-
C.
Dan Hannebery
Dan Hannebery is a former Australian rules footballer best known as a star midfielder for the Sydney Swans, where he became a premiership player and multiple All-Australian.
-
D.
Neale Hanvey
Neale Hanvey is a Scottish politician who has served as the Member of Parliament for the Kirkcaldy and Cowdenbeath constituency.
-
E.
Tim Haines
Tim Haines is a British television producer and director best known for creating groundbreaking prehistoric and natural history series that blend documentary storytelling with cutting-edge visual effects.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.