Triple
T18878907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amber Heard |
E461763
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Oonagh Paige Heard |
—
|
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: Oonagh Paige Heard | Statement: [Amber Heard, child, Oonagh Paige Heard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oonagh Paige Heard Context triple: [Amber Heard, child, Oonagh Paige Heard]
-
A.
Oonagh Paige Heard
chosen
Oonagh Paige Heard is the daughter of American actress Amber Heard, born via surrogate in 2021.
-
B.
Jennifer Naughton
Jennifer Naughton is a local political leader who serves as the mayor of Spring Lake, New Jersey.
-
C.
Jennifer Tighe
Jennifer Tighe is an American actress known for her work in television, film, and theater, and as the daughter of actor Kevin Tighe.
-
D.
Julia Ormond
Julia Ormond is a British actress known for her roles in films such as "Legends of the Fall," "Sabrina," and "The Curious Case of Benjamin Button."
-
E.
Nina Blount
Nina Blount is a glamorous, naive young socialite navigating the excesses and emotional upheavals of 1930s high society in the film "Bright Young Things."
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d06ef481908bba297d7a1fd011 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 10, 2026, 11:57 a.m.