Triple

T7114522
Position Surface form Disambiguated ID Type / Status
Subject Sofia University "St. Kliment Ohridski" E165785 entity
Predicate shortName P43 FINISHED
Object SU
SU is the common abbreviation for Sofia University "St. Kliment Ohridski," Bulgaria’s oldest and most prestigious higher education institution.
 E641744 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: SU | Statement: [Sofia University "St. Kliment Ohridski", shortName, SU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SU
Context triple: [Sofia University "St. Kliment Ohridski", shortName, SU]
  • A. SU
    SU was the two-letter country code used to represent the former Soviet Union in various international standards and systems.
  • B. SU
    SU is the commonly used abbreviation for Stockholm University, a major public research university in Stockholm, Sweden.
  • C. SU
    SU is the commonly used abbreviation for Saurashtra University, a public higher education institution located in Gujarat, India.
  • D. SU
    SU is the stock ticker symbol under which Schneider Electric, a global leader in energy management and automation, is traded.
  • E. SU
    SU is the station code used to identify Summerhill railway station.
  • 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: SU
Triple: [Sofia University "St. Kliment Ohridski", shortName, SU]
Generated description
SU is the common abbreviation for Sofia University "St. Kliment Ohridski," Bulgaria’s oldest and most prestigious higher education institution.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SU
Target entity description: SU is the common abbreviation for Sofia University "St. Kliment Ohridski," Bulgaria’s oldest and most prestigious higher education institution.
  • A. SU
    SU is the commonly used abbreviation for Stockholm University, a major public research university in Stockholm, Sweden.
  • B. SU
    SU is the commonly used abbreviation for Saurashtra University, a public higher education institution located in Gujarat, India.
  • C. SU
    SU was the two-letter country code used to represent the former Soviet Union in various international standards and systems.
  • D. SU
    SU is the IATA airline designator for Aeroflot, Russia’s flag carrier and largest airline.
  • E. SU
    SU is the stock ticker symbol under which Schneider Electric, a global leader in energy management and automation, is traded.
  • 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_69c6888227bc8190a1394679e3116f90 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e5f0dab8819092103aefcaa1f9c2 completed March 27, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79cbfc7a08190ab07f3d65aa79f16 completed March 28, 2026, 9:17 a.m.
NEDg Description generation batch_69c79d0215888190b0e59c2584358a05 completed March 28, 2026, 9:18 a.m.
NED2 Entity disambiguation (via description) batch_69c79d63b6dc8190b3b52ef6566ba490 completed March 28, 2026, 9:20 a.m.
Created at: March 27, 2026, 2:43 p.m.