Triple

T7672064
Position Surface form Disambiguated ID Type / Status
Subject Leigh Harline E173771 entity
Predicate familyName P18 FINISHED
Object Harline
Harline is a surname most notably associated with Leigh Harline, an American film composer known for his work with Walt Disney Studios.
E681716 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: Harline | Statement: [Leigh Harline, familyName, Harline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harline
Context triple: [Leigh Harline, familyName, Harline]
  • A. Harlean
    Harlean is the birth name of classic Hollywood film star Jean Harlow, a major sex symbol and leading actress of the 1930s.
  • B. Bauline
    Bauline is a small coastal town in Newfoundland and Labrador, Canada, located on the Avalon Peninsula near St. John’s.
  • C. Arliss
    "Arliss" is an American comedy television series that satirically follows a ruthless sports agent navigating the business and ethical dilemmas of professional athletics.
  • D. Ainley
    Ainley is an English surname most notably associated with actor Anthony Ainley, known for his role as the Master in the classic Doctor Who series.
  • E. Lainez
    Lainez is a Spanish-language surname of Basque origin borne by various notable figures in politics, sports, and the arts.
  • 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: Harline
Triple: [Leigh Harline, familyName, Harline]
Generated description
Harline is a surname most notably associated with Leigh Harline, an American film composer known for his work with Walt Disney Studios.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Harline
Target entity description: Harline is a surname most notably associated with Leigh Harline, an American film composer known for his work with Walt Disney Studios.
  • A. Harlean
    Harlean is the birth name of classic Hollywood film star Jean Harlow, a major sex symbol and leading actress of the 1930s.
  • B. Bauline
    Bauline is a small coastal town in Newfoundland and Labrador, Canada, located on the Avalon Peninsula near St. John’s.
  • C. Arliss
    "Arliss" is an American comedy television series that satirically follows a ruthless sports agent navigating the business and ethical dilemmas of professional athletics.
  • D. Ainley
    Ainley is an English surname most notably associated with actor Anthony Ainley, known for his role as the Master in the classic Doctor Who series.
  • E. Lainez
    Lainez is a Spanish-language surname of Basque origin borne by various notable figures in politics, sports, and the arts.
  • 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_69c699562484819086752091e3164a27 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701de94208190a7627521211452dc completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a22f74f481909498391bfaf23428 completed March 29, 2026, 3:53 a.m.
NEDg Description generation batch_69c8a34c93a081908ec3509c3abb3866 completed March 29, 2026, 3:58 a.m.
NED2 Entity disambiguation (via description) batch_69c8a3b4e0a88190ad525c83bd03e09f completed March 29, 2026, 3:59 a.m.
Created at: March 27, 2026, 4 p.m.