Triple

T5620050
Position Surface form Disambiguated ID Type / Status
Subject University of Szczecin E147577 entity
Predicate abbreviation P43 FINISHED
Object US
US is the commonly used abbreviation for the University of Szczecin, a public higher education institution in Szczecin, Poland.
 E531741 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: US | Statement: [University of Szczecin, abbreviation, US]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: US
Context triple: [University of Szczecin, abbreviation, US]
  • A. US
    US is the IATA airline designator code assigned to the former American airline US Airways.
  • B. US
    The US, or United States, is a federal republic in North America comprising 50 states and known as one of the world's largest economic and military powers.
  • C. US
    The US, or United States, is a large federal republic in North America composed of 50 states and known as one of the world's most influential economic and political powers.
  • D. US
    The US, or United States, is a large federal republic in North America composed of 50 states and known as a major global economic and political power.
  • E. US
    The US, or United States, is a federal republic in North America composed of 50 states and known as one of the world’s largest economic and military powers.
  • 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: US
Triple: [University of Szczecin, abbreviation, US]
Generated description
US is the commonly used abbreviation for the University of Szczecin, a public higher education institution in Szczecin, Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: US
Target entity description: US is the commonly used abbreviation for the University of Szczecin, a public higher education institution in Szczecin, Poland.
  • A. US
    The US, or United States, is a large federal republic in North America composed of 50 states and known as one of the world's most influential economic and political powers.
  • B. US
    The US, or United States, is a federal republic in North America comprising 50 states and known as one of the world's largest economic and military powers.
  • C. US
    The US, or United States, is a large federal republic in North America composed of 50 states and known as a major global economic and political power.
  • D. US
    US is the IATA airline designator code assigned to the former American airline US Airways.
  • E. US
    The US, or United States, is a federal republic in North America composed of 50 states and known as one of the world’s largest economic and military powers.
  • 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_69c00906f2a88190a992c66b13d606d4 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c022108db8819098739510366adee1 completed March 22, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027e57ed88190b2ff3245226851d1 completed March 22, 2026, 5:33 p.m.
NEDg Description generation batch_69c03c495bf88190884ab03b9e5540f0 completed March 22, 2026, 7 p.m.
NED2 Entity disambiguation (via description) batch_69c03cd550748190ab9718c510d2f0ca completed March 22, 2026, 7:02 p.m.
Created at: March 22, 2026, 3:40 p.m.