Triple

T13902497
Position Surface form Disambiguated ID Type / Status
Subject The Pass E334259 entity
Predicate filmEditingBy P14416 FINISHED
Object Mark Trend
Mark Trend is a film editor known for his work on the movie "The Pass."
E1068751 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: Mark Trend | Statement: [The Pass, filmEditingBy, Mark Trend]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Trend
Context triple: [The Pass, filmEditingBy, Mark Trend]
  • A. Mark Tarlov
    Mark Tarlov was an American film producer, director, and winemaker known for producing movies such as "Copycat" and later founding acclaimed Oregon wineries.
  • B. Mark Belt
    Mark Belt is the original name of the city now known as Pearland, Texas.
  • C. Mark Roule
    Mark Roule is a musician best known as a guitarist associated with the new wave band Tom Tom Club.
  • D. Mark Wendland
    Mark Wendland is an American scenic designer known for his innovative and visually striking sets for Broadway productions and other theatrical works.
  • E. Mark Seelig
    Mark Seelig is a musician and composer known for his work in ambient and shamanic music, often featuring overtone and devotional chanting.
  • 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: Mark Trend
Triple: [The Pass, filmEditingBy, Mark Trend]
Generated description
Mark Trend is a film editor known for his work on the movie "The Pass."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mark Trend
Target entity description: Mark Trend is a film editor known for his work on the movie "The Pass."
  • A. Mark Tarlov
    Mark Tarlov was an American film producer, director, and winemaker known for producing movies such as "Copycat" and later founding acclaimed Oregon wineries.
  • B. Mark Belt
    Mark Belt is the original name of the city now known as Pearland, Texas.
  • C. Mark Roule
    Mark Roule is a musician best known as a guitarist associated with the new wave band Tom Tom Club.
  • D. Mark Wendland
    Mark Wendland is an American scenic designer known for his innovative and visually striking sets for Broadway productions and other theatrical works.
  • E. Mark Seelig
    Mark Seelig is a musician and composer known for his work in ambient and shamanic music, often featuring overtone and devotional chanting.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de25d9c7a48190ad8fb0ca676f4f7b completed April 14, 2026, 11:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c722e72081909090b2d64000ebd9 completed May 3, 2026, 10:07 p.m.
NEDg Description generation batch_69f7c83a3e04819097b6e0b5a3161b9a completed May 3, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69f7c9732d188190a8a7151d21e0a310 completed May 3, 2026, 10:17 p.m.
Created at: April 9, 2026, 10:16 p.m.