Triple
T18252604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niven Howie |
E437131
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Get Lucky (2013 film) |
—
|
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: Get Lucky (2013 film) | Statement: [Niven Howie, notableWork, Get Lucky (2013 film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Get Lucky (2013 film) Context triple: [Niven Howie, notableWork, Get Lucky (2013 film)]
-
A.
Get Lucky
Get Lucky is a studio album by Australian rock group Little River Band, showcasing their soft rock and adult contemporary sound of the early 1990s.
-
B.
Get Lucky
chosen
"Get Lucky" is a globally successful 2013 disco-funk single by Daft Punk featuring Pharrell Williams and Nile Rodgers, known for its catchy groove and retro-inspired sound.
-
C.
How Lucky Can a Man Get
"How Lucky Can a Man Get" is a song featured on the album "Make a Move," likely known as one of its notable tracks.
-
D.
Lucky
"Lucky" is a rock album by American singer-songwriter Melissa Etheridge, known for its introspective lyrics and soulful, guitar-driven sound.
-
E.
Lucky
Lucky is a character in the crime drama film "Waist Deep," involved in the gritty, high-stakes world surrounding the protagonist.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd81ea3481909d96b5399f7a32b3 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:33 a.m.