Triple

T12276077
Position Surface form Disambiguated ID Type / Status
Subject Jane Setter E292591 entity
Predicate affiliation P10 FINISHED
Object Department of English Language and Applied Linguistics, University of Reading
The Department of English Language and Applied Linguistics at the University of Reading is an academic unit specializing in the study and teaching of English language, linguistics, and their practical applications in real-world contexts.
E976157 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: Department of English Language and Applied Linguistics, University of Reading | Statement: [Jane Setter, affiliation, Department of English Language and Applied Linguistics, University of Reading]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of English Language and Applied Linguistics, University of Reading
Context triple: [Jane Setter, affiliation, Department of English Language and Applied Linguistics, University of Reading]
  • A. School of Linguistics and Literary Studies
    The School of Linguistics and Literary Studies is an academic faculty at Osnabrück University specializing in language, linguistics, and literary scholarship.
  • B. Faculty of Applied Linguistics
    The Faculty of Applied Linguistics is a division of the University of Warsaw specializing in the study and teaching of foreign languages, translation, and practical language applications.
  • C. Department of Theoretical and Applied Linguistics, University of Cambridge
    The Department of Theoretical and Applied Linguistics at the University of Cambridge is a leading academic centre for research and teaching in linguistics, covering areas such as syntax, phonology, semantics, psycholinguistics, and language acquisition.
  • D. Faculty of English for Specific Purposes
    The Faculty of English for Specific Purposes is an academic unit at Foreign Trade University specializing in training students in professional and industry-focused English language skills.
  • E. School of Languages, Linguistics and Film, Queen Mary University of London
    The School of Languages, Linguistics and Film at Queen Mary University of London is an academic department specializing in the study and research of modern languages, linguistics, comparative literature, and film.
  • 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: Department of English Language and Applied Linguistics, University of Reading
Triple: [Jane Setter, affiliation, Department of English Language and Applied Linguistics, University of Reading]
Generated description
The Department of English Language and Applied Linguistics at the University of Reading is an academic unit specializing in the study and teaching of English language, linguistics, and their practical applications in real-world contexts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of English Language and Applied Linguistics, University of Reading
Target entity description: The Department of English Language and Applied Linguistics at the University of Reading is an academic unit specializing in the study and teaching of English language, linguistics, and their practical applications in real-world contexts.
  • A. School of Linguistics and Literary Studies
    The School of Linguistics and Literary Studies is an academic faculty at Osnabrück University specializing in language, linguistics, and literary scholarship.
  • B. Faculty of Applied Linguistics
    The Faculty of Applied Linguistics is a division of the University of Warsaw specializing in the study and teaching of foreign languages, translation, and practical language applications.
  • C. Department of Theoretical and Applied Linguistics, University of Cambridge
    The Department of Theoretical and Applied Linguistics at the University of Cambridge is a leading academic centre for research and teaching in linguistics, covering areas such as syntax, phonology, semantics, psycholinguistics, and language acquisition.
  • D. Faculty of English for Specific Purposes
    The Faculty of English for Specific Purposes is an academic unit at Foreign Trade University specializing in training students in professional and industry-focused English language skills.
  • E. School of Languages, Linguistics and Film, Queen Mary University of London
    The School of Languages, Linguistics and Film at Queen Mary University of London is an academic department specializing in the study and research of modern languages, linguistics, comparative literature, and film.
  • 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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf06cf08190ac8671dd9bbed03d completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e6d72d081908c8697257df712f1 completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f620759f348190baa9af5b33d4e37f completed May 2, 2026, 4:04 p.m.
NED2 Entity disambiguation (via description) batch_69f624bf23948190b182e4c31564d210 completed May 2, 2026, 4:22 p.m.
Created at: April 8, 2026, 9:52 p.m.