Triple

T9125895
Position Surface form Disambiguated ID Type / Status
Subject University of Medicine 1, Yangon E218966 entity
Predicate alsoKnownAs P39 FINISHED
Object UM1
UM1 is a leading medical university in Yangon, Myanmar, known for training physicians and conducting medical research.
 E779677 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: UM1 | Statement: [University of Medicine 1, Yangon, alsoKnownAs, UM1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UM1
Context triple: [University of Medicine 1, Yangon, alsoKnownAs, UM1]
  • A. UMI
    UMI is the three-letter ISO 3166-1 alpha-3 country code assigned to Kingman Reef, an uninhabited U.S. territory in the central Pacific Ocean.
  • B. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • C. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • D. UM
    UM is a public research university in Winnipeg, Canada, known as the University of Manitoba.
  • E. UM
    UM is a public research university in Oxford, Mississippi, commonly known as "Ole Miss" and recognized for its academic programs and SEC athletics.
  • 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: UM1
Triple: [University of Medicine 1, Yangon, alsoKnownAs, UM1]
Generated description
UM1 is a leading medical university in Yangon, Myanmar, known for training physicians and conducting medical research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UM1
Target entity description: UM1 is a leading medical university in Yangon, Myanmar, known for training physicians and conducting medical research.
  • A. UMI
    UMI is the three-letter ISO 3166-1 alpha-3 country code assigned to Kingman Reef, an uninhabited U.S. territory in the central Pacific Ocean.
  • B. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • C. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • D. UM
    UM is a public research university in Winnipeg, Canada, known as the University of Manitoba.
  • E. UM
    UM is a public research university in Oxford, Mississippi, commonly known as "Ole Miss" and recognized for its academic programs and SEC athletics.
  • 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_69ca83dddd548190983b96c664f7f367 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8b8970881909c3b2c67fc131627 completed April 1, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d030a1042c8190a31c76638a95a2cf completed April 3, 2026, 9:26 p.m.
NEDg Description generation batch_69d0318ef52c8190bfa0bef6a8d41daa completed April 3, 2026, 9:30 p.m.
NED2 Entity disambiguation (via description) batch_69d03571c4648190bd546152c61c55a5 completed April 3, 2026, 9:47 p.m.
Created at: March 30, 2026, 7:17 p.m.