Triple

T2804015
Position Surface form Disambiguated ID Type / Status
Subject Wicker Park E54009 entity
Predicate cinematographer P1953 FINISHED
Object Peter Sova E259291 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: Peter Sova | Statement: [Wicker Park, cinematographer, Peter Sova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Sova
Context triple: [Wicker Park, cinematographer, Peter Sova]
  • A. Peter Sova chosen
    Peter Sova was a Czech-American cinematographer known for his stylish visual work on films such as "Lucky Number Slevin" and collaborations with directors like Barry Levinson.
  • B. Mike Sokolsky
    Mike Sokolsky is a co-founder of the online education platform Udacity, known for its technology-focused courses and nanodegree programs.
  • C. Don Smolenski
    Don Smolenski is an American sports executive best known for serving as the president of the NFL’s Philadelphia Eagles, overseeing the franchise’s business operations.
  • D. Joe Pisarcik
    Joe Pisarcik is a former NFL quarterback best known for his infamous late-game fumble in 1978 that led to the "Miracle at the Meadowlands."
  • E. John Kundla
    John Kundla was a Hall of Fame American basketball coach best known for leading the Minneapolis Lakers to multiple early NBA championships.
  • 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde1409148190a06a401185a26b64 completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc674217c81908177b088cc824e7b completed March 10, 2026, 7:21 a.m.
Created at: March 6, 2026, 9:59 p.m.