Triple

T13695122
Position Surface form Disambiguated ID Type / Status
Subject Blunt Talk E328363 entity
Predicate character P662 FINISHED
Object Martin
Martin is a fictional character from the television comedy series "Blunt Talk."
E1054579 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: Martin | Statement: [Blunt Talk, character, Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martin
Context triple: [Blunt Talk, character, Martin]
  • A. Martin
    Martin is a minor but kind-hearted character in Ernest Hemingway's novella "The Old Man and the Sea," known for helping the old fisherman Santiago.
  • B. Martin
    Martin is a pessimistic scholar who serves as one of Candide’s key philosophical foils in Voltaire’s satirical novella "Candide."
  • C. Martin
    Martin is a character in Don DeLillo’s novel "Falling Man," which explores the personal and psychological aftermath of the September 11 attacks.
  • D. Martin
    Martin is a renowned brand of acoustic guitars and related instruments produced by C. F. Martin & Company.
  • E. Martin
    Martin is a brand best known for its Martin N-20 classical acoustic guitar, famously associated with Willie Nelson’s instrument “Trigger.”
  • 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: Martin
Triple: [Blunt Talk, character, Martin]
Generated description
Martin is a fictional character from the television comedy series "Blunt Talk."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Martin
Target entity description: Martin is a fictional character from the television comedy series "Blunt Talk."
  • A. Martin
    Martin is a key supporting character in the British comedy-drama series "Fleabag," known for his abrasive personality, inappropriate behavior, and tense relationship with the show's protagonist and her family.
  • B. Martin
    Martin is a 1990s American sitcom starring Martin Lawrence as a wisecracking Detroit radio DJ and later TV personality, known for its energetic humor and memorable supporting characters.
  • C. Martin
    Martin is a central character in Sam Shepard’s play "Fool for Love," often portrayed as an outsider whose presence heightens the tension and emotional conflict between the main protagonists.
  • D. Martin
    Martin is a character in Don DeLillo’s novel "Falling Man," which explores the personal and psychological aftermath of the September 11 attacks.
  • E. Martin
    Martin is a minor but kind-hearted character in Ernest Hemingway's novella "The Old Man and the Sea," known for helping the old fisherman Santiago.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8773f388190b2413b1e05fd5fd7 completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f794514afc8190b334b1fc74a6cdd5 completed May 3, 2026, 6:30 p.m.
NEDg Description generation batch_69f795e361c48190b37060312e7df181 completed May 3, 2026, 6:37 p.m.
NED2 Entity disambiguation (via description) batch_69f796e5c60c8190a19389bc4cdbd658 completed May 3, 2026, 6:41 p.m.
Created at: April 9, 2026, 9:54 p.m.