Triple
T10325508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Five Wives |
E242750
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Zoë Kravitz |
E171187
|
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: Zoë Kravitz | Statement: [The Five Wives, portrayedBy, Zoë Kravitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zoë Kravitz Context triple: [The Five Wives, portrayedBy, Zoë Kravitz]
-
A.
Zoë Kravitz
chosen
Zoë Kravitz is an American actress, singer, and model known for roles in films like "Mad Max: Fury Road," "Fantastic Beasts," and "The Batman," as well as for fronting the band Lolawolf.
-
B.
Mia Kirshner
Mia Kirshner is a Canadian actress known for her dark, nuanced performances in film and television, including her notable role in the crime drama "The Black Dahlia."
-
C.
Zoey Deutch
Zoey Deutch is an American actress known for her roles in films such as "Before I Fall," "Set It Up," and "Zombieland: Double Tap."
-
D.
Suki Waterhouse
Suki Waterhouse is an English model, actress, and singer known for her fashion work, film roles, and music career.
-
E.
Zendaya
Zendaya is an American actress and singer best known for her acclaimed, Emmy-winning performance as Rue Bennett in the HBO drama series "Euphoria."
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7cd76348190b93562112300acfc |
completed | April 7, 2026, 10:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e4cdf8881908d613a0cb65fa0c2 |
completed | April 10, 2026, 4:36 a.m. |
Created at: April 6, 2026, 11:51 a.m.