Triple

T9154140
Position Surface form Disambiguated ID Type / Status
Subject Babe Paley E219665 entity
Predicate nickname P55 FINISHED
Object Babe
Babe was the stylish socialite and fashion icon Babe Paley, renowned for her elegance and influence in mid-20th-century American high society.
 E781220 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: Babe | Statement: [Babe Paley, nickname, Babe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Babe
Context triple: [Babe Paley, nickname, Babe]
  • A. Babe
    Babe is the famous nickname of George Herman "Babe" Ruth, the legendary American baseball player widely regarded as one of the greatest hitters in the sport's history.
  • B. Babe
    "Babe" is a 1990s pop song by the British boy band Take That, known as one of their early hit ballads.
  • C. Babe
    Babe is a civil parish located within the municipality of Bragança in northeastern Portugal.
  • D. Babe
    Babe is a critically acclaimed 1995 family film that blends live-action and animatronics to tell the story of a pig who aspires to be a sheepdog.
  • E. Babe
    "Babe" is a novel by American author Marianne Wiggins, known for its inventive narrative voice and exploration of complex personal relationships.
  • 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: Babe
Triple: [Babe Paley, nickname, Babe]
Generated description
Babe was the stylish socialite and fashion icon Babe Paley, renowned for her elegance and influence in mid-20th-century American high society.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Babe
Target entity description: Babe was the stylish socialite and fashion icon Babe Paley, renowned for her elegance and influence in mid-20th-century American high society.
  • A. Babe
    Babe is the nickname of Babe Phelps, an American Major League Baseball catcher active in the 1930s and early 1940s.
  • B. Babe
    Babe is the famous nickname of George Herman "Babe" Ruth, the legendary American baseball player widely regarded as one of the greatest hitters in the sport's history.
  • C. Babe
    Babe is the nickname of Thomas "Babe" Levy, the fictional graduate student and marathon runner portrayed by Dustin Hoffman in the 1976 thriller film "Marathon Man."
  • D. Babe
    "Babe" is a novel by American author Marianne Wiggins, known for its inventive narrative voice and exploration of complex personal relationships.
  • E. Babe
    "Babe" is a 1990s pop song by the British boy band Take That, known as one of their early hit ballads.
  • 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_69ca83e25418819093c6503deeaf30de completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca96f87ac8190b2fc6d2b2834c1b6 completed April 1, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0484e580c8190944ad76f6ef0be9d completed April 3, 2026, 11:07 p.m.
NEDg Description generation batch_69d0496672a881909c1ac91a7ec1a2a1 completed April 3, 2026, 11:12 p.m.
NED2 Entity disambiguation (via description) batch_69d04a35451881909dfe6795b743b026 completed April 3, 2026, 11:16 p.m.
Created at: March 30, 2026, 7:20 p.m.