Triple

T15122388
Position Surface form Disambiguated ID Type / Status
Subject Never Say Never E361199 entity
Predicate cinematographyBy P1953 FINISHED
Object Thomas Kloss
Thomas Kloss is a cinematographer known for his work on feature films and music-related projects, including the concert film "Never Say Never."
E1174878 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: Thomas Kloss | Statement: [Never Say Never, cinematographyBy, Thomas Kloss]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas Kloss
Context triple: [Never Say Never, cinematographyBy, Thomas Kloss]
  • A. Martin Klotz
    Martin Klotz was an Austrian mountaineer known for being one of the first climbers to reach the summit of the Grossglockner, Austria’s highest peak.
  • B. Nigel Glockler
    Nigel Glockler is an English drummer best known for his long-standing role in the heavy metal band Saxon.
  • C. Richard Lohse
    Richard Lohse was a Swiss painter and graphic designer known for his influential role in concrete art and systematic, geometric abstraction in the 20th century.
  • D. Michael Schoeffling
    Michael Schoeffling is an American former actor and model best known for his role as Jake Ryan in the 1984 film "Sixteen Candles."
  • E. Michael Tuchner
    Michael Tuchner was a British film and television director known for his work on crime dramas and character-driven stories in the 1960s and 1970s.
  • 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: Thomas Kloss
Triple: [Never Say Never, cinematographyBy, Thomas Kloss]
Generated description
Thomas Kloss is a cinematographer known for his work on feature films and music-related projects, including the concert film "Never Say Never."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Thomas Kloss
Target entity description: Thomas Kloss is a cinematographer known for his work on feature films and music-related projects, including the concert film "Never Say Never."
  • A. Martin Klotz
    Martin Klotz was an Austrian mountaineer known for being one of the first climbers to reach the summit of the Grossglockner, Austria’s highest peak.
  • B. Nigel Glockler
    Nigel Glockler is an English drummer best known for his long-standing role in the heavy metal band Saxon.
  • C. Richard Lohse
    Richard Lohse was a Swiss painter and graphic designer known for his influential role in concrete art and systematic, geometric abstraction in the 20th century.
  • D. Michael Schoeffling
    Michael Schoeffling is an American former actor and model best known for his role as Jake Ryan in the 1984 film "Sixteen Candles."
  • E. Michael Tuchner
    Michael Tuchner was a British film and television director known for his work on crime dramas and character-driven stories in the 1960s and 1970s.
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0059f69a881909929a037a0eef702 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff8754ef408190be0e4ea5c35cf000 completed May 9, 2026, 7:13 p.m.
NEDg Description generation batch_69ff881731ac8190baa3cea2c9b7975b completed May 9, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_69ff88cfbe388190b20c426b4c745f92 completed May 9, 2026, 7:19 p.m.
Created at: April 10, 2026, 3:06 a.m.