Triple
T20516746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Because You’re Mine |
E503700
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Leonard Lee |
—
|
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: Leonard Lee | Statement: [Because You’re Mine, screenwriter, Leonard Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leonard Lee Context triple: [Because You’re Mine, screenwriter, Leonard Lee]
-
A.
Leonard Lee
chosen
Leonard Lee is a screenwriter known for his work on the film "The Maze."
-
B.
Leonard Leroy Lee
Leonard Leroy Lee is the birth name of American actor Robert Fuller, known for his roles in classic Western television series such as "Laramie" and "Wagon Train."
-
C.
Leonard Smith
Leonard Smith was an American cinematographer best known for his work on classic Hollywood films, including the Technicolor family drama "National Velvet."
-
D.
Leonard Gordon
Leonard Gordon was a cardiologist and manager best known as the longtime husband of acclaimed actress and EGOT-winning performer Rita Moreno.
-
E.
Leonard Rogers
Leonard Rogers was a prominent British physician and researcher in tropical medicine, particularly known for his work in India on cholera, dysentery, and kala-azar.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f42db688190a3ccfba5601e8bf3 |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.