Triple

T10325639
Position Surface form Disambiguated ID Type / Status
Subject Tully E242753 entity
Predicate cinematographyBy P1953 FINISHED
Object Eric Steelberg E317958 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: Eric Steelberg | Statement: [Tully, cinematographyBy, Eric Steelberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eric Steelberg
Context triple: [Tully, cinematographyBy, Eric Steelberg]
  • A. Eric Steelberg chosen
    Eric Steelberg is an American cinematographer known for his work on feature films such as "Juno," "Up in the Air," and "500 Days of Summer."
  • B. Joseph Silverstein
    Joseph Silverstein was an American violinist and conductor best known as concertmaster and later assistant conductor of the Boston Symphony Orchestra and as a prominent teacher.
  • C. Ian Siegel
    Ian Siegel is an American entrepreneur best known as the co-founder and longtime CEO of the online employment marketplace ZipRecruiter.
  • D. Max Steinberg
    Max Steinberg is an American professional poker player known for his success in World Series of Poker events, including winning a WSOP bracelet.
  • E. Jonathan Stern
    Jonathan Stern is an American film and television producer best known for his work on offbeat comedies such as "Wet Hot American Summer" and various projects for Adult Swim and streaming platforms.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d7cd76348190b93562112300acfc completed April 7, 2026, 10:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d95e4aef148190be58486605f85f77 completed April 10, 2026, 8:32 p.m.
Created at: April 6, 2026, 11:51 a.m.