Triple

T6618473
Position Surface form Disambiguated ID Type / Status
Subject University of San Francisco E149614 entity
Predicate mascot P52 FINISHED
Object The Don
The Don is the University of San Francisco’s Spanish-influenced, nobleman-themed athletic mascot representing the school’s sports teams.
E601105 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: The Don | Statement: [University of San Francisco, mascot, The Don]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Don
Context triple: [University of San Francisco, mascot, The Don]
  • A. Stalsk‑12
    Stalsk‑12 is a secretive, heavily fortified Russian closed city that serves as the climactic battleground in Christopher Nolan’s film "Tenet."
  • B. Krimzon Guard
    The Krimzon Guard is the authoritarian military police force in the Jak and Daxter video game series, known for enforcing Baron Praxis’s oppressive rule over Haven City.
  • C. Yuriatin
    Yuriatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Yuri Zhivago’s life and relationships.
  • D. Duma
    Duma is a 2005 family adventure film directed by Carroll Ballard about a boy and his close bond with an orphaned cheetah in South Africa.
  • E. Gorky Park
    Gorky Park is a famous central Moscow park known for its recreational facilities, cultural events, and scenic riverside location.
  • 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: The Don
Triple: [University of San Francisco, mascot, The Don]
Generated description
The Don is the University of San Francisco’s Spanish-influenced, nobleman-themed athletic mascot representing the school’s sports teams.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: The Don
Target entity description: The Don is the University of San Francisco’s Spanish-influenced, nobleman-themed athletic mascot representing the school’s sports teams.
  • A. Stalsk‑12
    Stalsk‑12 is a secretive, heavily fortified Russian closed city that serves as the climactic battleground in Christopher Nolan’s film "Tenet."
  • B. Krimzon Guard
    The Krimzon Guard is the authoritarian military police force in the Jak and Daxter video game series, known for enforcing Baron Praxis’s oppressive rule over Haven City.
  • C. Yuriatin
    Yuriatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Yuri Zhivago’s life and relationships.
  • D. Duma
    Duma is a 2005 family adventure film directed by Carroll Ballard about a boy and his close bond with an orphaned cheetah in South Africa.
  • E. Gorky Park
    Gorky Park is a 1983 crime thriller film, based on Martin Cruz Smith’s novel, about a Soviet detective investigating a triple murder in Moscow.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af5b21348190b7f09045e9ec7d63 completed March 27, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbde37288190b1e65589aa09b676 completed March 27, 2026, 6:26 p.m.
NEDg Description generation batch_69c6cd89b51c81909ea17d391732630e completed March 27, 2026, 6:33 p.m.
NED2 Entity disambiguation (via description) batch_69c6ce70442c8190a12a6c6eb76c5269 completed March 27, 2026, 6:37 p.m.
Created at: March 27, 2026, 1:58 p.m.