Triple

T3548797
Position Surface form Disambiguated ID Type / Status
Subject Utah Utes women's gymnastics E75059 entity
Predicate studentSectionName P11244 FINISHED
Object The MUSS
The MUSS is the energetic student fan section known for passionately supporting University of Utah athletics, including the Utah Utes women's gymnastics team.
 E366465 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 MUSS | Statement: [Utah Utes women's gymnastics, studentSectionName, The MUSS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The MUSS
Context triple: [Utah Utes women's gymnastics, studentSectionName, The MUSS]
  • A. Muster
    Muster, commonly known as Aggie Muster, is a cherished Texas A&M University tradition in which Aggies worldwide gather annually to honor and remember fellow Aggies who have passed away.
  • B. MU
    MU is the IATA airline designator assigned to China Eastern Airlines, one of China’s major carriers.
  • C. MU
    MU is the commonly used abbreviation for the University of Missouri, a major public research university based in Columbia, Missouri.
  • D. Munukutuba
    Munukutuba is a widely used Bantu lingua franca of the Republic of the Congo and surrounding regions, serving as a major language of trade and interethnic communication.
  • E. MUR
    MUR is the Italian Ministry responsible for national policies on universities, higher education, and scientific and technological research.
  • 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 MUSS
Triple: [Utah Utes women's gymnastics, studentSectionName, The MUSS]
Generated description
The MUSS is the energetic student fan section known for passionately supporting University of Utah athletics, including the Utah Utes women's gymnastics team.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: The MUSS
Target entity description: The MUSS is the energetic student fan section known for passionately supporting University of Utah athletics, including the Utah Utes women's gymnastics team.
  • A. Muster
    Muster, commonly known as Aggie Muster, is a cherished Texas A&M University tradition in which Aggies worldwide gather annually to honor and remember fellow Aggies who have passed away.
  • B. MU
    MU is the IATA airline designator assigned to China Eastern Airlines, one of China’s major carriers.
  • C. MU
    MU is the commonly used abbreviation for the University of Missouri, a major public research university based in Columbia, Missouri.
  • D. Munukutuba
    Munukutuba is a widely used Bantu lingua franca of the Republic of the Congo and surrounding regions, serving as a major language of trade and interethnic communication.
  • E. MUR
    MUR is the Italian Ministry responsible for national policies on universities, higher education, and scientific and technological research.
  • 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_69ad85d33c6c819081d5ac1df13b5680 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbfd278348190ad2fa54f4a423541 completed March 8, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38be582308190808274c8a530ce51 completed March 13, 2026, 4 a.m.
NEDg Description generation batch_69b38c6e70a88190805de417a8740d64 completed March 13, 2026, 4:02 a.m.
NED2 Entity disambiguation (via description) batch_69b38cd2c540819083d3188c2dea7283 completed March 13, 2026, 4:04 a.m.
Created at: March 8, 2026, 3:20 p.m.