Triple
T14489325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skillet |
E359321
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Unleashed |
E879197
|
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: Unleashed | Statement: [Skillet, notableWork, Unleashed]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unleashed Context triple: [Skillet, notableWork, Unleashed]
-
A.
Unleashed
chosen
Unleashed is a 2005 action-thriller film starring Jet Li as a brutal enforcer raised like a dog who seeks freedom and humanity after escaping his violent captor.
-
B.
Frenzy
Frenzy is a 1972 British thriller film directed by Alfred Hitchcock, known for its dark humor and disturbing portrayal of a serial killer in London.
-
C.
Frenzy
"Frenzy" is a popular Nigerian Afropop song by artist D'Prince, known for its energetic beat and club-friendly vibe.
-
D.
Frenzy
Frenzy is a Hearthstone keyword that triggers a special effect the first time a minion survives damage.
-
E.
Unleashed (2016 film)
Unleashed (2016 film) is an independent romantic comedy with a fantastical twist, in which a young woman’s cat and dog are transformed into human men, forcing her to reevaluate love and relationships.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930bd1d48190abd6c47da0a3ebc8 |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d90f86081908b25f3eb90042c73 |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 10, 2026, 1:20 a.m.