Triple
T17026787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heidi (1937 film) |
E413084
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Mary Nash |
—
|
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: Mary Nash | Statement: [Heidi (1937 film), castMember, Mary Nash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Nash Context triple: [Heidi (1937 film), castMember, Mary Nash]
-
A.
Mary Nash
chosen
Mary Nash was an American character actress known for her supporting roles in classic Hollywood films of the 1930s and 1940s.
-
B.
Sarah Nash
Sarah Nash is an American business executive known for her leadership roles in major retail and financial companies, including serving on the board and in senior positions at L Brands.
-
C.
Noreen Nash
Noreen Nash was an American film actress who appeared in numerous Hollywood productions during the 1940s and 1950s.
-
D.
Carol Denise Nash
Carol Denise Nash, better known as Niecy Nash, is an American actress, comedian, and television host recognized for her roles in series like "Reno 911!" and "Claws."
-
E.
Emma Norton
Emma Norton is a film and television producer best known for her work on acclaimed drama series such as the adaptation of Sally Rooney’s "Normal People."
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d5ed388190871aa738cac04b65 |
completed | April 18, 2026, 7:04 p.m. |
Created at: April 10, 2026, 5:33 a.m.