Triple

T13535477
Position Surface form Disambiguated ID Type / Status
Subject Zhytomyr Polytechnic State University E323248 entity
Predicate hasAbbreviation P43 FINISHED
Object ZPSU
ZPSU is a Ukrainian technical university known for engineering, technology, and applied sciences education and research.
 E1046584 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: ZPSU | Statement: [Zhytomyr Polytechnic State University, hasAbbreviation, ZPSU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZPSU
Context triple: [Zhytomyr Polytechnic State University, hasAbbreviation, ZPSU]
  • A. ZSU
    ZSU is the commonly used Ukrainian abbreviation for the Armed Forces of Ukraine, the country's unified military organization.
  • B. ZSP
    ZSP is the three-letter station code used to identify St James's Park tube station on the London Underground network.
  • C. UZS
    UZS is the official currency code for the Uzbekistani soʻm, the national currency of Uzbekistan.
  • D. ZS
    ZS is the vehicle registration code assigned to cars registered in the Polish city of Szczecin.
  • E. ZS
    ZS is the stock ticker symbol for Zscaler, a cloud-based information security company traded on the NASDAQ.
  • 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: ZPSU
Triple: [Zhytomyr Polytechnic State University, hasAbbreviation, ZPSU]
Generated description
ZPSU is a Ukrainian technical university known for engineering, technology, and applied sciences education and research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZPSU
Target entity description: ZPSU is a Ukrainian technical university known for engineering, technology, and applied sciences education and research.
  • A. ZSU
    ZSU is the commonly used Ukrainian abbreviation for the Armed Forces of Ukraine, the country's unified military organization.
  • B. ZSP
    ZSP is the three-letter station code used to identify St James's Park tube station on the London Underground network.
  • C. UZS
    UZS is the official currency code for the Uzbekistani soʻm, the national currency of Uzbekistan.
  • D. ZS
    ZS is the vehicle registration code assigned to cars registered in the Polish city of Szczecin.
  • E. ZS
    ZS is the stock ticker symbol for Zscaler, a cloud-based information security company traded on the NASDAQ.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafbcad2881909fb7490311807f75 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d9a448c81908fa57a909a9097f7 completed May 3, 2026, 2:37 p.m.
NEDg Description generation batch_69f75e7d8970819092116ae7a769ac21 completed May 3, 2026, 2:41 p.m.
NED2 Entity disambiguation (via description) batch_69f75f35c6008190b88e14feddb93a1d completed May 3, 2026, 2:44 p.m.
Created at: April 9, 2026, 9:44 p.m.