Triple
T3653377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mare of Easttown |
E77472
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Angourie Rice |
E163052
|
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: Angourie Rice | Statement: [Mare of Easttown, starring, Angourie Rice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angourie Rice Context triple: [Mare of Easttown, starring, Angourie Rice]
-
A.
Angourie Rice
chosen
Angourie Rice is an Australian actress known for her breakout role in "The Nice Guys" and for appearing in films such as "Spider-Man: Homecoming" and "Spider-Man: Far From Home."
-
B.
Suki Waterhouse
Suki Waterhouse is an English model, actress, and singer known for her fashion work, film roles, and music career.
-
C.
Mackenzie Davis
Mackenzie Davis is a Canadian actress known for her roles in films like "Blade Runner 2049" and "The Martian" and the TV series "Halt and Catch Fire."
-
D.
Natalie Desselle
Natalie Desselle was an American actress best known for her comedic roles in film and television, including her memorable performance in the 1997 adaptation of "Cinderella."
-
E.
Olivia Wilde
Olivia Wilde is an American actress and filmmaker known for her roles in film and television, including the medical drama "House" and for directing the acclaimed film "Booksmart."
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3b805a48190a7bc230a382365d6 |
completed | March 8, 2026, 6:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fafdfe108190a808364578d5edd1 |
completed | March 14, 2026, 6:06 a.m. |
Created at: March 8, 2026, 3:24 p.m.