Triple

T14328715
Position Surface form Disambiguated ID Type / Status
Subject The Free-Lance Pallbearers E355281 entity
Predicate character P662 FINISHED
Object Harry Sam
Harry Sam is a character in Ishmael Reed's satirical novel "The Free-Lance Pallbearers," representing one of the absurd, grotesque figures populating its dystopian political landscape.
E1094306 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: Harry Sam | Statement: [The Free-Lance Pallbearers, character, Harry Sam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harry Sam
Context triple: [The Free-Lance Pallbearers, character, Harry Sam]
  • A. Harry Betts
    Harry Betts was an American jazz trombonist, composer, and arranger known for his work in film and television scores.
  • B. Henry Samson
    Henry Samson was a young passenger on the Mayflower who later became a settler in Plymouth Colony in early 17th-century New England.
  • C. Harry Rowlands
    Harry Rowlands is known primarily as the husband of June Rowlands, the first female mayor of Toronto.
  • D. Harry Hendon
    Harry Hendon is a software developer known for creating the RMM1 system.
  • E. Harry Squire
    Harry Squire was a cinematographer best known for his work on the pioneering widescreen travelogue film "This Is Cinerama."
  • 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: Harry Sam
Triple: [The Free-Lance Pallbearers, character, Harry Sam]
Generated description
Harry Sam is a character in Ishmael Reed's satirical novel "The Free-Lance Pallbearers," representing one of the absurd, grotesque figures populating its dystopian political landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Harry Sam
Target entity description: Harry Sam is a character in Ishmael Reed's satirical novel "The Free-Lance Pallbearers," representing one of the absurd, grotesque figures populating its dystopian political landscape.
  • A. Harry Betts
    Harry Betts was an American jazz trombonist, composer, and arranger known for his work in film and television scores.
  • B. Henry Samson
    Henry Samson was a young passenger on the Mayflower who later became a settler in Plymouth Colony in early 17th-century New England.
  • C. Harry Rowlands
    Harry Rowlands is known primarily as the husband of June Rowlands, the first female mayor of Toronto.
  • D. Harry Hendon
    Harry Hendon is a software developer known for creating the RMM1 system.
  • E. Harry Squire
    Harry Squire was a cinematographer best known for his work on the pioneering widescreen travelogue film "This Is Cinerama."
  • 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8c1c3e70819084b6728ac5c18561 completed April 14, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd46927af48190b91095d852fcacbe completed May 8, 2026, 2:12 a.m.
NEDg Description generation batch_69fd47fa764c8190b1d691f5847b7a05 completed May 8, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69fd492226888190a014b23e506ab19c completed May 8, 2026, 2:23 a.m.
Created at: April 10, 2026, 1:13 a.m.