Triple

T2461592
Position Surface form Disambiguated ID Type / Status
Subject Paper Towns E54545 entity
Predicate cinematographer P1953 FINISHED
Object David Lanzenberg
David Lanzenberg is a film cinematographer known for his work on feature films such as "Paper Towns."
 E366661 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: David Lanzenberg | Statement: [Paper Towns, cinematographer, David Lanzenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: David Lanzenberg
Context triple: [Paper Towns, cinematographer, David Lanzenberg]
  • A. Michael Lehmann
    Michael Lehmann is an American film and television director best known for the dark comedy "Heathers" and various other Hollywood comedies.
  • B. Chris Lebenzon
    Chris Lebenzon is an American film editor known for his long-time collaborations with directors like Tim Burton and Tony Scott on major Hollywood films.
  • C. Sam Zussman
    Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
  • D. David Lubin
    David Lubin was a Polish-born American merchant, agricultural reformer, and internationalist best known for pioneering global agricultural cooperation and helping lay the groundwork for modern organizations like the FAO.
  • E. Steven Baigelman
    Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
  • 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: David Lanzenberg
Triple: [Paper Towns, cinematographer, David Lanzenberg]
Generated description
David Lanzenberg is a film cinematographer known for his work on feature films such as "Paper Towns."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: David Lanzenberg
Target entity description: David Lanzenberg is a film cinematographer known for his work on feature films such as "Paper Towns."
  • A. Michael Lehmann
    Michael Lehmann is an American film and television director best known for the dark comedy "Heathers" and various other Hollywood comedies.
  • B. Chris Lebenzon
    Chris Lebenzon is an American film editor known for his long-time collaborations with directors like Tim Burton and Tony Scott on major Hollywood films.
  • C. Sam Zussman
    Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
  • D. David Lubin
    David Lubin was a Polish-born American merchant, agricultural reformer, and internationalist best known for pioneering global agricultural cooperation and helping lay the groundwork for modern organizations like the FAO.
  • E. Steven Baigelman
    Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
  • 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_69ab49dee84c819096b50a0049c347ac completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd11c47408190b10c7f6a151f2db2 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69b38ba25b48819095d21bf9d2276042 completed March 13, 2026, 3:59 a.m.
NEDg Description generation batch_69b38c209d8c8190b644c8861d8874e3 completed March 13, 2026, 4:01 a.m.
NED2 Entity disambiguation (via description) batch_69b38c939c948190a137d79030d9c8d1 completed March 13, 2026, 4:03 a.m.
Created at: March 6, 2026, 9:44 p.m.