Triple

T3174929
Position Surface form Disambiguated ID Type / Status
Subject The Ox-Bow Incident E66438 entity
Predicate castMember P1668 FINISHED
Object Marc Lawrence
Marc Lawrence was an American character actor best known for his frequent portrayals of gangsters and tough guys in classic Hollywood films.
E348977 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: Marc Lawrence | Statement: [The Ox-Bow Incident, castMember, Marc Lawrence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marc Lawrence
Context triple: [The Ox-Bow Incident, castMember, Marc Lawrence]
  • A. Sam Lawson
    Sam Lawson is a fictional New England storyteller created by Harriet Beecher Stowe, known for his humorous, dialect-rich tales in "Oldtown Fireside Stories."
  • B. Ian Ritchie
    Ian Ritchie is a British architect known for his innovative, high-tech designs and for leading the practice Ian Ritchie Architects.
  • C. Scott Lambert
    Scott Lambert is a film producer known for his work on the drama film "North Country."
  • D. Graeme Revell
    Graeme Revell is a New Zealand-born composer best known for his atmospheric film scores across genres including horror, action, and science fiction.
  • E. Mark Carlisle
    Mark Carlisle was a British Conservative politician who served in senior government roles, including as Secretary of State for Education and Science under Prime Minister Margaret Thatcher.
  • 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: Marc Lawrence
Triple: [The Ox-Bow Incident, castMember, Marc Lawrence]
Generated description
Marc Lawrence was an American character actor best known for his frequent portrayals of gangsters and tough guys in classic Hollywood films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Marc Lawrence
Target entity description: Marc Lawrence was an American character actor best known for his frequent portrayals of gangsters and tough guys in classic Hollywood films.
  • A. Sam Lawson
    Sam Lawson is a fictional New England storyteller created by Harriet Beecher Stowe, known for his humorous, dialect-rich tales in "Oldtown Fireside Stories."
  • B. Ian Ritchie
    Ian Ritchie is a British architect known for his innovative, high-tech designs and for leading the practice Ian Ritchie Architects.
  • C. Scott Lambert
    Scott Lambert is a film producer known for his work on the drama film "North Country."
  • D. Graeme Revell
    Graeme Revell is a New Zealand-born composer best known for his atmospheric film scores across genres including horror, action, and science fiction.
  • E. Mark Carlisle
    Mark Carlisle was a British Conservative politician who served in senior government roles, including as Secretary of State for Education and Science under Prime Minister Margaret Thatcher.
  • 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_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada671e6848190a683eec1519b9268 completed March 8, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a6206988190a6aaecbfe8ccf0bf completed March 12, 2026, 7:56 p.m.
NEDg Description generation batch_69b31aded5808190afbe4ae3ddb70428 completed March 12, 2026, 7:58 p.m.
NED2 Entity disambiguation (via description) batch_69b31c4665c081908d96878fc257fb76 completed March 12, 2026, 8:04 p.m.
Created at: March 8, 2026, 3:06 p.m.