Triple
T22975289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Green Bay Tree |
E571298
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Helen Haye |
—
|
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: Helen Haye | Statement: [The Green Bay Tree, castMember, Helen Haye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Haye Context triple: [The Green Bay Tree, castMember, Helen Haye]
-
A.
Helen Haye
chosen
Helen Haye was a British stage and film actress known for her character roles in early 20th-century theatre and cinema.
-
B.
Helene Evans
Helene Evans is known as the wife of American football wide receiver Mike Evans.
-
C.
Anna Hardie
Anna Hardie is a central fictional character in Ali Smith’s novel "There But For The," around whom much of the story’s emotional and thematic exploration revolves.
-
D.
Helen Gilbert
Helen Gilbert was an American actress and singer active in the 1930s and 1940s, known for her roles in Hollywood films and musical performances.
-
E.
Helen Gibbins
Helen Gibbins is an individual whose specific public background or notable achievements are not clearly identifiable from the available information.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18235de508190ab9675d005870ff6 |
completed | April 29, 2026, 3:59 a.m. |
Created at: April 17, 2026, 3:48 p.m.