Triple
T20248166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master of None |
E498478
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Naomi Ackie |
—
|
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: Naomi Ackie | Statement: [Master of None, starring, Naomi Ackie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naomi Ackie Context triple: [Master of None, starring, Naomi Ackie]
-
A.
Naomi Ackie
chosen
Naomi Ackie is a British actress known for her acclaimed performances in film, television, and theatre, including roles in productions such as "Lady Macbeth" and "Star Wars: The Rise of Skywalker."
-
B.
Maria Riva
Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
-
C.
Gemma Chan
Gemma Chan is a British actress known for her roles in films such as "Crazy Rich Asians," "Eternals," and various acclaimed television dramas.
-
D.
Emily Patterson
Emily Patterson is the daughter of American actress Téa Leoni.
-
E.
Alannah Henriksen
Alannah Henriksen is the daughter of American actor Lance Henriksen, known for his roles in science fiction and horror films.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673a5ce4081908dff86ed4c613fd6 |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 11, 2026, 11:40 p.m.