Triple

T3674305
Position Surface form Disambiguated ID Type / Status
Subject Adam Mickiewicz University in Poznań E77951 entity
Predicate abbreviation P43 FINISHED
Object UAM
UAM is a major public research university in Poznań, Poland, named after the poet Adam Mickiewicz and known as one of the country’s leading academic institutions.
 E377490 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: UAM | Statement: [Adam Mickiewicz University in Poznań, abbreviation, UAM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UAM
Context triple: [Adam Mickiewicz University in Poznań, abbreviation, UAM]
  • A. UAM
    UAM is the IATA airport code for Andersen Air Force Base, a major United States Air Force installation on Guam.
  • B. UAM
    UAM is a major Spanish public research university located in Madrid, known for its strong academic programs and international reputation.
  • C. UAQ
    UAQ is the vehicle registration code used on license plates issued in the emirate of Umm Al Quwain in the United Arab Emirates.
  • D. UAK
    UAK was the temporary currency code used for the Ukrainian karbovanets, a transitional currency of Ukraine in the early 1990s before the introduction of the hryvnia.
  • E. UCA
    UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
  • 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: UAM
Triple: [Adam Mickiewicz University in Poznań, abbreviation, UAM]
Generated description
UAM is a major public research university in Poznań, Poland, named after the poet Adam Mickiewicz and known as one of the country’s leading academic institutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UAM
Target entity description: UAM is a major public research university in Poznań, Poland, named after the poet Adam Mickiewicz and known as one of the country’s leading academic institutions.
  • A. UAM
    UAM is the IATA airport code for Andersen Air Force Base, a major United States Air Force installation on Guam.
  • B. UAM
    UAM is a major Spanish public research university located in Madrid, known for its strong academic programs and international reputation.
  • C. UAQ
    UAQ is the vehicle registration code used on license plates issued in the emirate of Umm Al Quwain in the United Arab Emirates.
  • D. UAK
    UAK was the temporary currency code used for the Ukrainian karbovanets, a transitional currency of Ukraine in the early 1990s before the introduction of the hryvnia.
  • E. UCA
    UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
  • 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_69ad85e083008190b2e1b7085fe500bd completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc45fbd1c819099023791452f1beb completed March 8, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48854a2308190ba6a9fc39929b35c completed March 13, 2026, 9:57 p.m.
NEDg Description generation batch_69b48b48c5f48190b9db5f3feca08e0e completed March 13, 2026, 10:10 p.m.
NED2 Entity disambiguation (via description) batch_69b4af0410e8819091cb1259d06d60cc completed March 14, 2026, 12:42 a.m.
Created at: March 8, 2026, 3:25 p.m.