Triple
T20386268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Good Mother |
E497963
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Daniel Melnick |
—
|
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: Daniel Melnick | Statement: [The Good Mother, producer, Daniel Melnick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Melnick Context triple: [The Good Mother, producer, Daniel Melnick]
-
A.
Daniel Melnick
chosen
Daniel Melnick was an American film and television producer known for overseeing influential movies such as “Network,” “All That Jazz,” and “Altered States.”
-
B.
Bruce E. Melnick
Bruce E. Melnick is a former NASA astronaut and U.S. Coast Guard officer who flew as a mission specialist on two Space Shuttle missions in the early 1990s.
-
C.
Peter Melnick
Peter Melnick is an American composer known for his film and television scores, including his work on the romantic comedy "L.A. Story."
-
D.
Michael Weinberg
Michael Weinberg is a television and film producer best known for his executive production work on the series "Heartland."
-
E.
Michael Braverman
Michael Braverman is a television producer best known for his work as an executive producer on reality and documentary-style TV series.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790bcef481909453d19c846ab420 |
completed | April 20, 2026, 7:05 p.m. |
Created at: April 16, 2026, 11:28 a.m.