Triple
T18077916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nick Hurran |
E432605
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Little Black Book |
—
|
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: Little Black Book | Statement: [Nick Hurran, directed, Little Black Book]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Little Black Book Context triple: [Nick Hurran, directed, Little Black Book]
-
A.
Little Black Book
chosen
Little Black Book is a 2004 romantic comedy film about a woman who secretly investigates her boyfriend’s ex-girlfriends, featuring Ron Livingston in a key role.
-
B.
Black Book
Black Book is a 2006 Dutch World War II thriller film directed by Paul Verhoeven, acclaimed for its gripping espionage story and moral complexity.
-
C.
Black Book
Black Book is a jazz album by saxophonist Greg Osby, showcasing his innovative, modern approach to post-bop and improvisation.
-
D.
Blue Book
Blue Book is the fictional tech company in the film "Ex Machina," a powerful search-engine giant whose secretive AI research drives the movie’s plot.
-
E.
The Memory Book
The Memory Book is a popular self-help guide that teaches practical memory-improvement and study techniques to enhance recall and learning.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f6a85481909894c39c8be98d5d |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:26 a.m.