Triple
T22899536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phillip Noyce |
E568270
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Lucy Noyce |
—
|
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: Lucy Noyce | Statement: [Phillip Noyce, child, Lucy Noyce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucy Noyce Context triple: [Phillip Noyce, child, Lucy Noyce]
-
A.
Lucy Noyce
chosen
Lucy Noyce is known as the daughter of Australian film director Phillip Noyce.
-
B.
Tania Saulnier
Tania Saulnier is a Canadian actress best known for her leading role in the horror-comedy film "Slither."
-
C.
Rachel Hurd-Wood
Rachel Hurd-Wood is an English actress known for her roles in films such as "Peter Pan" and "Perfume: The Story of a Murderer."
-
D.
Amy Seimetz
Amy Seimetz is an American actress, writer, director, and producer known for her work in independent film and television, including co-creating and directing the series "The Girlfriend Experience."
-
E.
Sophia Takal
Sophia Takal is an American filmmaker and actress known for her work in independent cinema, including directing the 2019 horror remake "Black Christmas."
- 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180155b1c8190a83eb6ec45387a1a |
completed | April 29, 2026, 3:50 a.m. |
Created at: April 17, 2026, 3:41 p.m.