Triple
T7437304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iris Law |
E171646
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Sadie Frost |
E108075
|
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: Sadie Frost | Statement: [Iris Law, hasRelative, Sadie Frost]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sadie Frost Context triple: [Iris Law, hasRelative, Sadie Frost]
-
A.
Sadie Frost
chosen
Sadie Frost is an English actress, producer, and fashion designer known for her roles in films like "Bram Stoker's Dracula" and for co-founding the fashion label Frost French.
-
B.
Joanna Blunt
Joanna Blunt is the mother of British actress Emily Blunt and a member of the Blunt family connected to the entertainment industry.
-
C.
Anne Durkan
Anne Durkan is a notable individual associated with the Durkan family name, recognized as a bearer of this surname.
-
D.
Clare Barber
Clare Barber is a fictional character portrayed by actress Viveca Lindfors in the film "Welcome to L.A."
-
E.
Emily Beecham
Emily Beecham is a British-American actress known for her versatile performances in film and television, including prominent roles in projects such as "Little Joe," "Into the Badlands," and various independent and genre films.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f349399c8190b46d5882ece2e73a |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83449b84c81909167f29e901c0881 |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:13 p.m.