Triple
T10890497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emma Donoghue |
E257159
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Denis Donoghue |
E892200
|
NE FINISHED |
How this triple was built (2 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: Denis Donoghue | Statement: [Emma Donoghue, relative, Denis Donoghue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denis Donoghue Context triple: [Emma Donoghue, relative, Denis Donoghue]
-
A.
Denis Donoghue
chosen
Denis Donoghue was a prominent Irish literary critic and scholar known for his influential work on modern literature and aesthetics.
-
B.
Francis Kermode
Francis Kermode was a Canadian naturalist and museum curator best known for his work in British Columbia, after whom the rare white-furred Kermode bear is named.
-
C.
John Sutherland
John Sutherland is a prominent British literary critic and scholar known for his extensive work on Victorian literature and popular literary history.
-
D.
Malcolm Godden
Malcolm Godden is a distinguished British scholar of Old English and Anglo-Saxon literature, noted for his influential academic work and leadership in the field.
-
E.
Anthony Pym
Anthony Pym is a translation studies scholar known for his influential work on translation theory, intercultural communication, and translator training.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d752041e2c8190b513dc9dc5857fcc |
completed | April 9, 2026, 7:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2169ea02c8190addf125ec5adafe8 |
completed | April 17, 2026, 11:16 a.m. |
Created at: April 8, 2026, 9:21 p.m.