Triple

T1298624
Position Surface form Disambiguated ID Type / Status
Subject Milwaukee Bucks E27710 entity
Predicate mascot P52 FINISHED
Object Bango
Bango is the energetic deer mascot of the NBA's Milwaukee Bucks, known for his acrobatic dunks and fan entertainment during games.
 E149492 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: Bango | Statement: [Milwaukee Bucks, mascot, Bango]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bango
Context triple: [Milwaukee Bucks, mascot, Bango]
  • A. Banga
    Banga is an Indian-origin surname most prominently associated with Ajay Banga, the business executive and current President of the World Bank.
  • B. Bica
    Bica is a party involved in the U.S. Supreme Court case De Canas v. Bica, which addressed state authority over the employment of undocumented immigrants.
  • C. Bugotu
    Bugotu is an Austronesian language of the Meso-Melanesian subgroup spoken primarily on Santa Isabel Island in the Solomon Islands.
  • D. Gooba
    "Gooba" is a 2020 comeback single by American rapper Tekashi 6ix9ine, known for its aggressive style, colorful visuals, and massive online streaming numbers.
  • E. Beng
    Beng is the ISO 15924 four-letter code that designates the Bengali script used for writing the Bengali language and several other languages of the Indian subcontinent.
  • 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: Bango
Triple: [Milwaukee Bucks, mascot, Bango]
Generated description
Bango is the energetic deer mascot of the NBA's Milwaukee Bucks, known for his acrobatic dunks and fan entertainment during games.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bango
Target entity description: Bango is the energetic deer mascot of the NBA's Milwaukee Bucks, known for his acrobatic dunks and fan entertainment during games.
  • A. Banga
    Banga is an Indian-origin surname most prominently associated with Ajay Banga, the business executive and current President of the World Bank.
  • B. Bica
    Bica is a party involved in the U.S. Supreme Court case De Canas v. Bica, which addressed state authority over the employment of undocumented immigrants.
  • C. Bugotu
    Bugotu is an Austronesian language of the Meso-Melanesian subgroup spoken primarily on Santa Isabel Island in the Solomon Islands.
  • D. Gooba
    "Gooba" is a 2020 comeback single by American rapper Tekashi 6ix9ine, known for its aggressive style, colorful visuals, and massive online streaming numbers.
  • E. Beng
    Beng is the ISO 15924 four-letter code that designates the Bengali script used for writing the Bengali language and several other languages of the Indian subcontinent.
  • 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_69a496d6682881909ba658f1c1e0e2b0 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c111a76c81909e6b914694986251 completed March 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb30292dc8190a33fd62c997c3f1b completed March 7, 2026, 11:21 p.m.
NEDg Description generation batch_69acb42dd7488190935d289907e5ed91 completed March 7, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_69acb48a873081909a9d4d27ed8b7a7a completed March 7, 2026, 11:28 p.m.
Created at: March 1, 2026, 7:51 p.m.