Triple
T18234049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love and Learn |
E436621
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Alex Gottlieb |
—
|
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: Alex Gottlieb | Statement: [Love and Learn, producer, Alex Gottlieb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alex Gottlieb Context triple: [Love and Learn, producer, Alex Gottlieb]
-
A.
Alex Gottlieb
chosen
Alex Gottlieb was an American film producer and screenwriter active during Hollywood’s mid-20th-century studio era.
-
B.
Morton Gottlieb
Morton Gottlieb was an American theatrical and film producer best known for his work on acclaimed stage plays and character-driven movies.
-
C.
Max Rosenthal
Max Rosenthal is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Rosenthal.
-
D.
Philip Liebmann
Philip Liebmann was the husband of American film actress Linda Darnell.
-
E.
Bert Glatstein
Bert Glatstein is a film editor known for his work on the cult science-fiction comedy film "Forbidden Zone."
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b512a88190aa493b0793ab28b3 |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 10, 2026, 10:33 a.m.