Triple

T3681788
Position Surface form Disambiguated ID Type / Status
Subject Poznań University of Technology E78128 entity
Predicate shortName P43 FINISHED
Object PP
PP is the commonly used abbreviation for Poznań University of Technology, a major technical university located in Poznań, Poland.
 E379865 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: PP | Statement: [Poznań University of Technology, shortName, PP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PP
Context triple: [Poznań University of Technology, shortName, PP]
  • A. PP
    The ITU Plenipotentiary Conference (PP) is the top policy-making body of the International Telecommunication Union, where member states set the Union’s general policies, strategic direction, and leadership.
  • B. PP
    PP is the commonly used abbreviation for the People's Party, a major conservative political party in Spain.
  • C. P
    P is the vehicle registration code used on license plates for the Czech city of Plzeň.
  • D. PPR
    PPR is the commonly used abbreviation for Philadelphia Parks & Recreation, the municipal department that manages the city’s parks, recreation centers, and related public programs.
  • E. PPR
    PPR was the communist political party that led Poland in the final years of World War II and laid the foundations for the postwar socialist state.
  • 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: PP
Triple: [Poznań University of Technology, shortName, PP]
Generated description
PP is the commonly used abbreviation for Poznań University of Technology, a major technical university located in Poznań, Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PP
Target entity description: PP is the commonly used abbreviation for Poznań University of Technology, a major technical university located in Poznań, Poland.
  • A. PP
    The ITU Plenipotentiary Conference (PP) is the top policy-making body of the International Telecommunication Union, where member states set the Union’s general policies, strategic direction, and leadership.
  • B. PP
    PP is the commonly used abbreviation for the People's Party, a major conservative political party in Spain.
  • C. P
    P is the vehicle registration code used on license plates for the Czech city of Plzeň.
  • D. PPR
    PPR is the commonly used abbreviation for Philadelphia Parks & Recreation, the municipal department that manages the city’s parks, recreation centers, and related public programs.
  • E. PPR
    PPR was the communist political party that led Poland in the final years of World War II and laid the foundations for the postwar socialist state.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc492aed481909e8986378ad283fc completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3b306c081909b3857daa4f97ce2 completed March 14, 2026, 2:10 a.m.
NEDg Description generation batch_69b4c56b76ac81909ae8d2ef10b8ed28 completed March 14, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69b4c62f7b7c81909150d8e40bb2dda4 completed March 14, 2026, 2:21 a.m.
Created at: March 8, 2026, 3:25 p.m.