Triple
T13076228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Verhoeven |
E329582
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Black Book |
E816425
|
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: Black Book | Statement: [Paul Verhoeven, notableWork, Black Book]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Black Book Context triple: [Paul Verhoeven, notableWork, Black Book]
-
A.
Black Book
chosen
Black Book is a 2006 Dutch World War II thriller film directed by Paul Verhoeven, acclaimed for its gripping espionage story and moral complexity.
-
B.
Black Book
Black Book is a jazz album by saxophonist Greg Osby, showcasing his innovative, modern approach to post-bop and improvisation.
-
C.
Blow
Blow is a track by the American heavy metal band Bastard, known for its aggressive sound and raw energy.
-
D.
Blow
Blow is a 2001 crime drama film that chronicles the rise and fall of American cocaine smuggler George Jung within the 1970s–1980s drug trade.
-
E.
Blow
"Blow" is a disco-funk inspired song by Beyoncé, known for its sensual lyrics, retro production, and vibrant roller-disco themed visuals.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98117209081908272021013df2222 |
completed | April 10, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d608a2288190bf07023a5303f887 |
completed | May 3, 2026, 4:58 a.m. |
Created at: April 9, 2026, 9:01 p.m.