Triple

T16723970
Position Surface form Disambiguated ID Type / Status
Subject Whiskey Tango Foxtrot E406420 entity
Predicate basedOn P98 FINISHED
Object Kim Barker memoir
The Kim Barker memoir is a journalist’s humorous and candid account of her experiences reporting from Afghanistan and Pakistan during the war on terror.
 E1231309 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: Kim Barker memoir | Statement: [Whiskey Tango Foxtrot, basedOn, Kim Barker memoir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kim Barker memoir
Context triple: [Whiskey Tango Foxtrot, basedOn, Kim Barker memoir]
  • A. Kim Barker
    Kim Barker is an American screenwriter best known for writing the romantic comedy film "License to Wed."
  • B. Barker
    Barker is a surname most famously associated with Bob Barker, the longtime host of the American television game show "The Price Is Right."
  • C. Barker
    Barker was a prestigious British coachbuilding firm renowned for crafting luxurious custom bodies for high-end automobiles in the early 20th century.
  • D. Barker
    Barker is an Australian federal electoral division in South Australia, known for encompassing extensive rural and regional communities.
  • E. Andrew Barker
    Andrew Barker is a British electronic musician best known as a member of the influential Manchester acid house and techno group 808 State.
  • 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: Kim Barker memoir
Triple: [Whiskey Tango Foxtrot, basedOn, Kim Barker memoir]
Generated description
The Kim Barker memoir is a journalist’s humorous and candid account of her experiences reporting from Afghanistan and Pakistan during the war on terror.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kim Barker memoir
Target entity description: The Kim Barker memoir is a journalist’s humorous and candid account of her experiences reporting from Afghanistan and Pakistan during the war on terror.
  • A. Kim Barker
    Kim Barker is an American screenwriter best known for writing the romantic comedy film "License to Wed."
  • B. Barker
    Barker is a surname most famously associated with Bob Barker, the longtime host of the American television game show "The Price Is Right."
  • C. Barker
    Barker was a prestigious British coachbuilding firm renowned for crafting luxurious custom bodies for high-end automobiles in the early 20th century.
  • D. Barker
    Barker is an Australian federal electoral division in South Australia, known for encompassing extensive rural and regional communities.
  • E. Andrew Barker
    Andrew Barker is a British electronic musician best known as a member of the influential Manchester acid house and techno group 808 State.
  • 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38745d2048190b476e5aa83ec7fec completed April 18, 2026, 1:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d43c49081908eca922da8f90793 completed May 10, 2026, 2:59 p.m.
NEDg Description generation batch_6a00a19d8dc08190be5d750f71b083dc completed May 10, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_6a00a269cacc81909d084c5d3497a4e6 completed May 10, 2026, 3:21 p.m.
Created at: April 10, 2026, 5:20 a.m.