Triple

T13108594
Position Surface form Disambiguated ID Type / Status
Subject Department of Mechanical Engineering (University of Michigan) E310911 entity
Predicate hasAbbreviation P43 FINISHED
Object UM ME
UM ME is the Department of Mechanical Engineering at the University of Michigan, a leading academic unit known for research and education in mechanical and related engineering fields.
E1021764 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: UM ME | Statement: [Department of Mechanical Engineering (University of Michigan), hasAbbreviation, UM ME]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UM ME
Context triple: [Department of Mechanical Engineering (University of Michigan), hasAbbreviation, UM ME]
  • A. UMMM
    UMMM is the ICAO airport code assigned to Minsk-1 Airport in Minsk, Belarus.
  • B. UMM
    UMM is a private Islamic university in Malang, Indonesia, affiliated with the Muhammadiyah organization and known for its wide range of academic programs.
  • C. UMM
    UMM is a small public liberal arts college campus of the University of Minnesota system located in Morris, Minnesota.
  • D. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • E. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • 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: UM ME
Triple: [Department of Mechanical Engineering (University of Michigan), hasAbbreviation, UM ME]
Generated description
UM ME is the Department of Mechanical Engineering at the University of Michigan, a leading academic unit known for research and education in mechanical and related engineering fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: UM ME
Target entity description: UM ME is the Department of Mechanical Engineering at the University of Michigan, a leading academic unit known for research and education in mechanical and related engineering fields.
  • A. UMMM
    UMMM is the ICAO airport code assigned to Minsk-1 Airport in Minsk, Belarus.
  • B. UMM
    UMM is a private Islamic university in Malang, Indonesia, affiliated with the Muhammadiyah organization and known for its wide range of academic programs.
  • C. UMM
    UMM is a small public liberal arts college campus of the University of Minnesota system located in Morris, Minnesota.
  • D. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • E. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817ce07881909ec552bf861ac175 completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27bd8fc8190a81130b7cb3a8bd8 completed May 3, 2026, 5:51 a.m.
NEDg Description generation batch_69f6e37023d48190ba6a0b790ed23370 completed May 3, 2026, 5:56 a.m.
NED2 Entity disambiguation (via description) batch_69f6e40a13c8819084daf9b77b46a181 completed May 3, 2026, 5:58 a.m.
Created at: April 9, 2026, 9:05 p.m.