Triple
T5342890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WandaVision |
E123983
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Elizabeth Olsen |
E213244
|
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: Elizabeth Olsen | Statement: [WandaVision, starring, Elizabeth Olsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Olsen Context triple: [WandaVision, starring, Elizabeth Olsen]
-
A.
Elizabeth Olsen
chosen
Elizabeth Olsen is an American actress best known for portraying Wanda Maximoff / Scarlet Witch in the Marvel Cinematic Universe.
-
B.
Hayley Atwell
Hayley Atwell is a British-American actress best known for portraying Peggy Carter in the Marvel Cinematic Universe.
-
C.
Tessa Thompson
Tessa Thompson is an American actress known for her versatile performances in film and television, including prominent roles in projects like "Creed," "Thor: Ragnarok," and "Westworld."
-
D.
Brie Larson
Brie Larson is an Academy Award–winning American actress known for her versatile performances in films such as Room, Captain Marvel, and Kong: Skull Island.
-
E.
Jessica Henwick
Jessica Henwick is a British actress known for her roles in genre franchises such as "Game of Thrones," "Star Wars: The Force Awakens," and various action and science fiction films and 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_69bd464be27081908807b40b75c1bbae |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85cc5a9881909e23bf9c5b697a8e |
completed | March 20, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18cc387c8190a9fe430fe5bb38ce |
completed | March 21, 2026, 10:16 p.m. |
Created at: March 20, 2026, 2:01 p.m.