Triple
T22427400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Room |
E554407
|
entity |
| Predicate | producedBy |
P490
|
FINISHED |
| Object | Emma Donoghue |
—
|
NE NERFINISHED |
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: Emma Donoghue | Statement: [Room, producedBy, Emma Donoghue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emma Donoghue Context triple: [Room, producedBy, Emma Donoghue]
-
A.
Emma Donoghue
chosen
Emma Donoghue is an Irish-Canadian novelist, playwright, and screenwriter best known for her novel "Room" and its acclaimed film adaptation.
-
B.
Anne Enright
Anne Enright is an acclaimed contemporary Irish novelist and short story writer, best known for her Booker Prize–winning novel "The Gathering."
-
C.
A. L. Kennedy
A. L. Kennedy is a Scottish writer and stand-up comedian known for her darkly comic, psychologically incisive fiction and essays.
-
D.
Maeve Binchy
Maeve Binchy was a bestselling Irish novelist and short story writer known for her warm, character-driven tales of everyday life and relationships, often set in small-town Ireland.
-
E.
Claire Finn
Claire Finn is a skilled and compassionate chief medical officer aboard the exploratory spaceship in the science-fiction comedy-drama series "The Orville."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2e438481908d43026727afa709 |
completed | April 29, 2026, 1:09 a.m. |
Created at: April 16, 2026, 8:47 p.m.