Triple
T8492932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runaround |
E201016
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Speedy |
E180637
|
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: Speedy | Statement: [Runaround, featuresCharacter, Speedy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Speedy Context triple: [Runaround, featuresCharacter, Speedy]
-
A.
Speedy
chosen
Speedy is a 1928 silent comedy film starring Harold Lloyd, known for its energetic New York City setting and memorable Coney Island and baseball sequences.
-
B.
Quick Fast
"Quick Fast" is a hip-hop track by the California rap duo Audio Push, known for its energetic delivery and West Coast-influenced production.
-
C.
Faster
Faster is a 2010 American action thriller film starring Dwayne Johnson as an ex-con seeking revenge after his brother’s murder.
-
D.
Quick
Quick is the fast-talking, street-smart protagonist played by Eddie Murphy in the 1989 crime-comedy film "Harlem Nights."
-
E.
Fast
Fast is a surname most notably associated with American novelist and screenwriter Howard Fast, known for his historical and political works.
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe579b7088190b297b04527e36a2b |
completed | March 31, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce3a5c260c8190bc7012a04363d260 |
completed | April 2, 2026, 9:43 a.m. |
Created at: March 30, 2026, 6:13 p.m.