Triple
T11498526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Marvel |
E272605
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Elizabeth Marvel |
E272605
|
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 Marvel | Statement: [Elizabeth Marvel, name, Elizabeth Marvel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Marvel Context triple: [Elizabeth Marvel, name, Elizabeth Marvel]
-
A.
Elizabeth Marvel
chosen
Elizabeth Marvel is an American actress known for her versatile performances in film, television, and theater, including prominent roles in series like Homeland and House of Cards.
-
B.
Amy Ruck
Amy Ruck was the wife of botanist Francis Darwin, son of Charles Darwin, and a member of the extended Darwin family circle in late 19th-century England.
-
C.
Melissa Cobb
Melissa Cobb is an American film producer best known for her work on major animated features, including the Kung Fu Panda franchise.
-
D.
Beth Riesgraf
Beth Riesgraf is an American actress best known for playing the quirky thief Parker on the television series "Leverage."
-
E.
Lynn Collins
Lynn Collins is an American actress known for her roles in films such as X-Men Origins: Wolverine and John Carter, as well as various television 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de27db081909ccdb4ab0ef75bdb |
completed | April 10, 2026, 2:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e624d666c081908253cea4e2da1a4a |
completed | April 20, 2026, 1:06 p.m. |
Created at: April 8, 2026, 9:36 p.m.