Triple
T3287463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Facinelli |
E69016
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Fastlane
Fastlane is an early-2000s American action-crime television series known for its flashy style, high-octane car chases, and undercover cop storyline.
|
E345545
|
NE FINISHED |
How this triple was built (4 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: Fastlane | Statement: [Peter Facinelli, notableWork, Fastlane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fastlane Context triple: [Peter Facinelli, notableWork, Fastlane]
-
A.
Speedy
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.
Accelerate
Accelerate is a song by the Christian rock band Liberation, known for its energetic style and uplifting, faith-centered lyrics.
-
C.
Lightning Lane
Lightning Lane is Disney's expedited attraction entry system that allows guests to bypass regular standby lines at select theme park rides and experiences.
-
D.
Fast Life
"Fast Life" is a hip-hop track by American rapper Paul Wall that showcases his signature Southern rap style and themes of hustle and street luxury.
-
E.
Quick
Quick is the fast-talking, street-smart protagonist played by Eddie Murphy in the 1989 crime-comedy film "Harlem Nights."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Fastlane Triple: [Peter Facinelli, notableWork, Fastlane]
Generated description
Fastlane is an early-2000s American action-crime television series known for its flashy style, high-octane car chases, and undercover cop storyline.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fastlane Target entity description: Fastlane is an early-2000s American action-crime television series known for its flashy style, high-octane car chases, and undercover cop storyline.
-
A.
Speedy
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.
Accelerate
Accelerate is a song by the Christian rock band Liberation, known for its energetic style and uplifting, faith-centered lyrics.
-
C.
Lightning Lane
Lightning Lane is Disney's expedited attraction entry system that allows guests to bypass regular standby lines at select theme park rides and experiences.
-
D.
Fast Life
"Fast Life" is a hip-hop track by American rapper Paul Wall that showcases his signature Southern rap style and themes of hustle and street luxury.
-
E.
Quick
Quick is the fast-talking, street-smart protagonist played by Eddie Murphy in the 1989 crime-comedy film "Harlem Nights."
- F. None of above. chosen
Provenance (5 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb058e00881908fdf0a23208860d4 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e85f71508190b194b4d383d7ee32 |
completed | March 12, 2026, 4:22 p.m. |
| NEDg | Description generation | batch_69b2e8d165488190bdb6c07257f7502a |
completed | March 12, 2026, 4:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2ecfd3c20819089bc0b2141aee8eb |
completed | March 12, 2026, 4:42 p.m. |
Created at: March 8, 2026, 3:10 p.m.