Triple

T6411934
Position Surface form Disambiguated ID Type / Status
Subject George K. Zipf E127726 entity
Predicate familyName P18 FINISHED
Object Zipf
Zipf is a surname most notably associated with linguist George Kingsley Zipf, known for formulating Zipf's law about word frequency distributions.
 E592076 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: Zipf | Statement: [George K. Zipf, familyName, Zipf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zipf
Context triple: [George K. Zipf, familyName, Zipf]
  • A. Dunbar
    Dunbar is a coastal town in East Lothian, Scotland, historically notable as the site of major battles including a key clash in the English Civil Wars.
  • B. Bryc
    Bryc is an alternative spelling of the given name Bryce, typically used as a modern or stylistic variant.
  • C. Kleinburg
    Kleinburg is a historic, affluent village within the city of Vaughan, Ontario, known for its charming main street and the McMichael Canadian Art Collection.
  • D. Kimball
    Kimball is a small town located in McDowell County in the southern part of West Virginia, historically tied to the coal mining industry.
  • E. Kimball
    Kimball is the northern terminal station of Chicago's CTA Brown Line, serving the Albany Park neighborhood with rail connections to downtown.
  • 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: Zipf
Triple: [George K. Zipf, familyName, Zipf]
Generated description
Zipf is a surname most notably associated with linguist George Kingsley Zipf, known for formulating Zipf's law about word frequency distributions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zipf
Target entity description: Zipf is a surname most notably associated with linguist George Kingsley Zipf, known for formulating Zipf's law about word frequency distributions.
  • A. Dunbar
    Dunbar is a coastal town in East Lothian, Scotland, historically notable as the site of major battles including a key clash in the English Civil Wars.
  • B. Bryc
    Bryc is an alternative spelling of the given name Bryce, typically used as a modern or stylistic variant.
  • C. Kleinburg
    Kleinburg is a historic, affluent village within the city of Vaughan, Ontario, known for its charming main street and the McMichael Canadian Art Collection.
  • D. Kimball
    Kimball is a small town located in McDowell County in the southern part of West Virginia, historically tied to the coal mining industry.
  • E. Kimball
    Kimball is the northern terminal station of Chicago's CTA Brown Line, serving the Albany Park neighborhood with rail connections to downtown.
  • 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_69c0083723d88190b1e37b19df162c08 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068d228208190ba05eeb7707482fe completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640c48e688190981a19ce5eb2af44 completed March 27, 2026, 8:33 a.m.
NEDg Description generation batch_69c6427c80c48190b87b9ecd1e10e78a completed March 27, 2026, 8:40 a.m.
NED2 Entity disambiguation (via description) batch_69c642da89a48190a2d6de237669ca8c completed March 27, 2026, 8:42 a.m.
Created at: March 22, 2026, 4:42 p.m.