Triple

T12680785
Position Surface form Disambiguated ID Type / Status
Subject Bill Kunkel E302940 entity
Predicate familyName P18 FINISHED
Object Kunkel
Kunkel is a German-origin surname borne by various notable individuals across fields such as sports, science, and the arts.
 E997177 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: Kunkel | Statement: [Bill Kunkel, familyName, Kunkel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kunkel
Context triple: [Bill Kunkel, familyName, Kunkel]
  • A. Kugler
    Kugler is a German-language surname borne by various notable individuals across fields such as history, the arts, and public life.
  • B. Koppelman
    Koppelman is a surname most notably associated with American screenwriter, director, and producer Brian Koppelman.
  • C. Gribskov
    Gribskov is one of Denmark’s largest and oldest forests, known for its diverse woodland landscapes, rich wildlife, and extensive network of walking and cycling trails.
  • D. Hufstedler
    Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
  • E. Knisely
    Knisely is a surname most notably associated with Nicholas Knisely, an American Episcopal bishop and religious leader.
  • 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: Kunkel
Triple: [Bill Kunkel, familyName, Kunkel]
Generated description
Kunkel is a German-origin surname borne by various notable individuals across fields such as sports, science, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kunkel
Target entity description: Kunkel is a German-origin surname borne by various notable individuals across fields such as sports, science, and the arts.
  • A. Kugler
    Kugler is a German-language surname borne by various notable individuals across fields such as history, the arts, and public life.
  • B. Koppelman
    Koppelman is a surname most notably associated with American screenwriter, director, and producer Brian Koppelman.
  • C. Gribskov
    Gribskov is one of Denmark’s largest and oldest forests, known for its diverse woodland landscapes, rich wildlife, and extensive network of walking and cycling trails.
  • D. Hufstedler
    Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
  • E. Knisely
    Knisely is a surname most notably associated with Nicholas Knisely, an American Episcopal bishop and religious leader.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961b32dbc81908101fc5f07e26ed3 completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671a54b008190b02f9585d6c6ff77 completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f67285019c8190be831d3f72cf121f completed May 2, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_69f67323a724819092425cdb3a070b96 completed May 2, 2026, 9:56 p.m.
Created at: April 9, 2026, 5:21 p.m.