Triple
T10085236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayley Atwell |
E215202
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Hayley Atwell |
E215202
|
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: Hayley Atwell | Statement: [Hayley Atwell, name, Hayley Atwell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hayley Atwell Context triple: [Hayley Atwell, name, Hayley Atwell]
-
A.
Hayley Atwell
chosen
Hayley Atwell is a British-American actress best known for portraying Peggy Carter in the Marvel Cinematic Universe.
-
B.
Elizabeth Olsen
Elizabeth Olsen is an American actress best known for portraying Wanda Maximoff / Scarlet Witch 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.
Jessica Raine
Jessica Raine is a British actress best known for her television work, including prominent roles in series such as "Call the Midwife" and various high-profile dramas.
-
E.
Scarlett Johansson
Scarlett Johansson is an American actress known for her versatile film roles, including major parts in the Marvel Cinematic Universe and acclaimed performances in both independent and blockbuster movies.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd04609748190987a9364a387fa61 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b68188c48190ac783cdfc072c502 |
completed | April 5, 2026, 7:22 p.m. |
Created at: March 30, 2026, 9 p.m.