Triple

T5741286
Position Surface form Disambiguated ID Type / Status
Subject License to Wed E126619 entity
Predicate producer P490 FINISHED
Object Arnold Messer
Arnold Messer is a film producer known for his work on movies such as "License to Wed."
 E551163 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: Arnold Messer | Statement: [License to Wed, producer, Arnold Messer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Arnold Messer
Context triple: [License to Wed, producer, Arnold Messer]
  • A. Arnold Messer
    Arnold Messer is a film producer best known for his work on the crime thriller "Zodiac."
  • B. Arnold W. Messer
    Arnold W. Messer is a film producer known for his work on notable movies including the psychological thriller "Black Swan."
  • C. Arnold Schlaet
    Arnold Schlaet was an American businessman best known as a co-founder of the oil company that became Texaco.
  • D. Paul Schatz
    Paul Schatz was a German engineer and inventor best known for discovering the invertible cube and developing related kinetic geometric sculptures.
  • E. Werner R. Heymann
    Werner R. Heymann was a German composer best known for his sophisticated film scores in Hollywood’s Golden Age, particularly for classic comedies and romances.
  • 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: Arnold Messer
Triple: [License to Wed, producer, Arnold Messer]
Generated description
Arnold Messer is a film producer known for his work on movies such as "License to Wed."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Arnold Messer
Target entity description: Arnold Messer is a film producer known for his work on movies such as "License to Wed."
  • A. Arnold Messer
    Arnold Messer is a film producer best known for his work on the crime thriller "Zodiac."
  • B. Arnold W. Messer
    Arnold W. Messer is a film producer known for his work on notable movies including the psychological thriller "Black Swan."
  • C. Arnold Schlaet
    Arnold Schlaet was an American businessman best known as a co-founder of the oil company that became Texaco.
  • D. Paul Schatz
    Paul Schatz was a German engineer and inventor best known for discovering the invertible cube and developing related kinetic geometric sculptures.
  • E. Werner R. Heymann
    Werner R. Heymann was a German composer best known for his sophisticated film scores in Hollywood’s Golden Age, particularly for classic comedies and romances.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0258382908190af8787feb1e5fbcd completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a16436588190943a0b81ea9429d9 completed March 23, 2026, 2:11 a.m.
NEDg Description generation batch_69c0a210d9788190b3a40e8ec2f2c6b6 completed March 23, 2026, 2:14 a.m.
NED2 Entity disambiguation (via description) batch_69c0a2afcef88190a77c8089a1b85393 completed March 23, 2026, 2:17 a.m.
Created at: March 22, 2026, 3:48 p.m.