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.