Triple
T20409683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dylanesque |
E500555
|
entity |
| Predicate | precededBy |
P97
|
FINISHED |
| Object | Frantic |
—
|
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: Frantic | Statement: [Dylanesque, precededBy, Frantic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frantic Context triple: [Dylanesque, precededBy, Frantic]
-
A.
Frantic
chosen
Frantic is a 1988 neo-noir thriller film directed by Roman Polanski, starring Harrison Ford as an American doctor searching for his missing wife in Paris.
-
B.
Frenzy
Frenzy is a Hearthstone keyword that triggers a special effect the first time a minion survives damage.
-
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 1972 British thriller film directed by Alfred Hitchcock, known for its dark humor and disturbing portrayal of a serial killer in London.
-
E.
Frenzy
Frenzy is a small, hyperactive Decepticon known for his disruptive tactics, espionage skills, and penchant for causing chaos in the Transformers universe.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3e0c1c8190be39d7f09c839dfa |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:29 a.m.