Triple

T17073421
Position Surface form Disambiguated ID Type / Status
Subject Maureen Callahan E414279 entity
Predicate hasWrittenFor P11775 FINISHED
Object Sassy
Sassy was an influential American teen magazine from the late 1980s and early 1990s known for its feminist, alternative take on youth culture and media.
 E1249562 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: Sassy | Statement: [Maureen Callahan, hasWrittenFor, Sassy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sassy
Context triple: [Maureen Callahan, hasWrittenFor, Sassy]
  • A. Sassy
    Sassy is the nickname of Sarah Vaughan, the legendary American jazz singer renowned for her rich, expressive voice and virtuosic vocal technique.
  • B. Bossy
    "Bossy" is a 2006 hip hop/R&B song by Kelis featuring Too $hort, known for its confident lyrics and catchy, bass-heavy production.
  • C. Bossy
    Bossy is a surname most famously associated with Mike Bossy, the legendary Canadian ice hockey goal-scorer for the New York Islanders.
  • D. Cocky
    Cocky was the nickname of Eddie Collins, a Hall of Fame American Major League Baseball second baseman renowned for his hitting, speed, and intelligent play in the early 20th century.
  • E. Cocky
    Cocky is the costumed rooster mascot that represents the University of South Carolina Gamecocks at athletic events and school functions.
  • 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: Sassy
Triple: [Maureen Callahan, hasWrittenFor, Sassy]
Generated description
Sassy was an influential American teen magazine from the late 1980s and early 1990s known for its feminist, alternative take on youth culture and media.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sassy
Target entity description: Sassy was an influential American teen magazine from the late 1980s and early 1990s known for its feminist, alternative take on youth culture and media.
  • A. Sassy
    Sassy is the nickname of Sarah Vaughan, the legendary American jazz singer renowned for her rich, expressive voice and virtuosic vocal technique.
  • B. Bossy
    "Bossy" is a 2006 hip hop/R&B song by Kelis featuring Too $hort, known for its confident lyrics and catchy, bass-heavy production.
  • C. Bossy
    Bossy is a surname most famously associated with Mike Bossy, the legendary Canadian ice hockey goal-scorer for the New York Islanders.
  • D. Cocky
    Cocky was the nickname of Eddie Collins, a Hall of Fame American Major League Baseball second baseman renowned for his hitting, speed, and intelligent play in the early 20th century.
  • E. Cocky
    Cocky is the costumed rooster mascot that represents the University of South Carolina Gamecocks at athletic events and school functions.
  • 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_69d886cef44c8190ba56c44b4e863e64 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbc28fec81909c39d432094d9cdd completed April 18, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012ede108881909ddd0455be53ffac completed May 11, 2026, 1:20 a.m.
NEDg Description generation batch_6a012fe2a1b081909483baef845cc2c1 completed May 11, 2026, 1:24 a.m.
NED2 Entity disambiguation (via description) batch_6a0130c2ad9881909d8a8b64ebb59aa6 completed May 11, 2026, 1:28 a.m.
Created at: April 10, 2026, 5:34 a.m.