Triple
T22258333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ice Road |
E550149
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Amber Midthunder |
—
|
NE NERFINISHED |
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: Amber Midthunder | Statement: [The Ice Road, starring, Amber Midthunder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amber Midthunder Context triple: [The Ice Road, starring, Amber Midthunder]
-
A.
Amber Midthunder
chosen
Amber Midthunder is an American actress known for her roles in genre television and film, including prominent performances in series like Legion and the film Prey.
-
B.
Kiernan Shipka
Kiernan Shipka is an American actress best known for her leading roles in the series Mad Men and Chilling Adventures of Sabrina.
-
C.
Brianne Tju
Brianne Tju is an American actress known for her roles in teen and horror television series and films, including the thriller "47 Meters Down: Uncaged."
-
D.
Alexandra Billings
Alexandra Billings is an American actress, singer, and groundbreaking transgender performer best known for her work on stage and in television series such as "Transparent."
-
E.
Melora Hardin
Melora Hardin is an American actress and singer best known for her roles in television series such as "The Office" and "Monk," as well as numerous film and stage performances.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c4bff48190b4be83f5f7677ac8 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.