Triple

T541504
Position Surface form Disambiguated ID Type / Status
Subject Leiden University E12639 entity
Predicate abbreviation P43 FINISHED
Object LEI
LEI is the commonly used abbreviation for Leiden University, one of the oldest and most prestigious universities in the Netherlands.
 E68009 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: LEI | Statement: [Leiden University, abbreviation, LEI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LEI
Context triple: [Leiden University, abbreviation, LEI]
  • A. LTRI
    LTRI is a Japanese institution responsible for the professional training and research development of legal professionals, particularly judges and prosecutors.
  • B. LI
    LI is the Roman numeral representing the number 51.
  • C. LCC
    LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
  • D. LERU
    LERU is a consortium of leading European research-intensive universities that collaborates to influence research policy and promote high-quality academic research and education in Europe.
  • E. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • 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: LEI
Triple: [Leiden University, abbreviation, LEI]
Generated description
LEI is the commonly used abbreviation for Leiden University, one of the oldest and most prestigious universities in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LEI
Target entity description: LEI is the commonly used abbreviation for Leiden University, one of the oldest and most prestigious universities in the Netherlands.
  • A. LTRI
    LTRI is a Japanese institution responsible for the professional training and research development of legal professionals, particularly judges and prosecutors.
  • B. LI
    LI is the Roman numeral representing the number 51.
  • C. LCC
    LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
  • D. LERU
    LERU is a consortium of leading European research-intensive universities that collaborates to influence research policy and promote high-quality academic research and education in Europe.
  • E. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49861195081909540eaf402a5401a completed March 1, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4cc5d690881908742b313f28a0012 completed March 1, 2026, 11:31 p.m.
NEDg Description generation batch_69a4cea9d11881908f4bac61c7e63e82 completed March 1, 2026, 11:41 p.m.
NED2 Entity disambiguation (via description) batch_69a4cf5649588190949250ee800d921f completed March 1, 2026, 11:44 p.m.
Created at: March 1, 2026, 7:32 p.m.