Triple

T14769451
Position Surface form Disambiguated ID Type / Status
Subject UW E347088 entity
Predicate hasVariant P455 FINISHED
Object Wisco
Wisco is an informal nickname commonly used to refer to the University of Wisconsin or the state of Wisconsin.
E1118773 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: Wisco | Statement: [UW, hasVariant, Wisco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wisco
Context triple: [UW, hasVariant, Wisco]
  • A. Vilas
    Vilas is the surname of Guillermo Vilas, the legendary Argentine tennis player renowned for his clay-court dominance in the 1970s.
  • B. Comasco
    Comasco is a variety of the Lombard language traditionally spoken in and around the city of Como in northern Italy.
  • C. Durkee
    Durkee is a small historic unincorporated community in Baker County, Oregon, that developed as a stage stop and later a railroad and highway point along key transportation routes.
  • D. Washburn
    Washburn is a surname of English origin borne by various notable individuals across politics, industry, academia, and the arts.
  • E. Owaneco
    Owaneco was a prominent Mohegan sachem (chief) known for his leadership and land dealings in colonial New England during the late 17th and early 18th centuries.
  • 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: Wisco
Triple: [UW, hasVariant, Wisco]
Generated description
Wisco is an informal nickname commonly used to refer to the University of Wisconsin or the state of Wisconsin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wisco
Target entity description: Wisco is an informal nickname commonly used to refer to the University of Wisconsin or the state of Wisconsin.
  • A. Vilas
    Vilas is the surname of Guillermo Vilas, the legendary Argentine tennis player renowned for his clay-court dominance in the 1970s.
  • B. Comasco
    Comasco is a variety of the Lombard language traditionally spoken in and around the city of Como in northern Italy.
  • C. Durkee
    Durkee is a small historic unincorporated community in Baker County, Oregon, that developed as a stage stop and later a railroad and highway point along key transportation routes.
  • D. Washburn
    Washburn is a surname of English origin borne by various notable individuals across politics, industry, academia, and the arts.
  • E. Owaneco
    Owaneco was a prominent Mohegan sachem (chief) known for his leadership and land dealings in colonial New England during the late 17th and early 18th centuries.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec81236f081908063bb4350b7b985 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cf86730819082cf3f502ec16a46 completed May 8, 2026, 4:19 p.m.
NEDg Description generation batch_69fe1874682881909ff97bca55bea320 completed May 8, 2026, 5:08 p.m.
NED2 Entity disambiguation (via description) batch_69fe1918fa988190b8ed746aa6f6f829 completed May 8, 2026, 5:10 p.m.
Created at: April 10, 2026, 1:30 a.m.