Triple
T16761021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Young Girls of Rochefort |
E407342
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Grover Dale |
E728202
|
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: Grover Dale | Statement: [The Young Girls of Rochefort, stars, Grover Dale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grover Dale Context triple: [The Young Girls of Rochefort, stars, Grover Dale]
-
A.
Grover Dale
chosen
Grover Dale is an American actor, dancer, and choreographer known for his work on Broadway and in film and television.
-
B.
Arthur Leland
Arthur Leland was a prominent figure significant enough in his community or field to have the notable Leland Tower named in his honor.
-
C.
Grover Wolfe
Grover Wolfe was the older brother of American novelist Thomas Wolfe, remembered primarily through his connection to the writer’s life and family background.
-
D.
Grover Maxwell
Grover Maxwell was an American philosopher of science known for his influential work on scientific realism and the nature of theoretical entities.
-
E.
Grover Muldoon
Grover Muldoon is a brash, fast-talking New Yorker and car enthusiast from the 1976 comedy film "Silver Streak," known for helping the protagonist during a cross-country train adventure.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abec638c81909d71ff452a4123c9 |
completed | April 18, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52d077081908080c61da67e0032 |
completed | May 10, 2026, 3:33 p.m. |
Created at: April 10, 2026, 5:21 a.m.