Triple
T985004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Only Lovers Left Alive |
E21258
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Mia Wasikowska |
E99787
|
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: Mia Wasikowska | Statement: [Only Lovers Left Alive, starring, Mia Wasikowska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mia Wasikowska Context triple: [Only Lovers Left Alive, starring, Mia Wasikowska]
-
A.
Mia Wasikowska
chosen
Mia Wasikowska is an Australian actress known for her versatile performances in films such as "Alice in Wonderland," "Jane Eyre," and various independent dramas.
-
B.
Rooney Mara
Rooney Mara is an American actress known for her acclaimed performances in films such as "The Girl with the Dragon Tattoo" and "Carol."
-
C.
Alicia Vikander
Alicia Vikander is a Swedish actress known for her acclaimed performances in films such as "Ex Machina," "The Danish Girl," and "Tomb Raider."
-
D.
Kristen Stewart
Kristen Stewart is an American actress best known for her role as Bella Swan in the "Twilight" film series and for her acclaimed performances in independent and arthouse films.
-
E.
Jennifer Lawrence
Jennifer Lawrence is an American actress acclaimed for her versatile performances in films such as "Silver Linings Playbook" and "The Hunger Games" series.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4289acc88190886ac8971297b1f8 |
completed | March 7, 2026, 3:21 p.m. |
Created at: March 1, 2026, 7:41 p.m.