Triple
T16252948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Bennett |
E394557
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Naomi Watts |
E103014
|
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: Naomi Watts | Statement: [Maria Bennett, portrayedBy, Naomi Watts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naomi Watts Context triple: [Maria Bennett, portrayedBy, Naomi Watts]
-
A.
Naomi Watts
chosen
Naomi Watts is an acclaimed British-Australian actress known for her emotionally intense performances in films such as "Mulholland Drive," "The Ring," and "21 Grams."
-
B.
Rachel McAdams
Rachel McAdams is a Canadian actress known for her versatile performances in films such as "Mean Girls," "The Notebook," and "Spotlight."
-
C.
Jennifer Connelly
Jennifer Connelly is an American actress acclaimed for her versatile performances in films ranging from independent dramas to major Hollywood productions, including her Oscar-winning role in "A Beautiful Mind."
-
D.
Kate Bosworth
Kate Bosworth is an American actress best known for her roles in films such as "Blue Crush" and "Superman Returns."
-
E.
Naomi Groves
Naomi Groves is a notable individual recognized for bearing the surname Groves, though specific widely known public achievements or roles associated with her are not well documented.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24597b74481908fdb8175628a57a1 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ee788f88190b16d267f1eee6d62 |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:04 a.m.