Triple
T3785096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Opposite of Sex |
E85511
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Don Roos |
E387839
|
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: Don Roos | Statement: [The Opposite of Sex, screenwriter, Don Roos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Roos Context triple: [The Opposite of Sex, screenwriter, Don Roos]
-
A.
Don Roos
chosen
Don Roos is an American screenwriter and film director known for his sharp, darkly comedic dramas such as "The Opposite of Sex" and "Happy Endings."
-
B.
Thomas Rongen
Thomas Rongen is a Dutch-American soccer coach and former player known for his extensive coaching career in Major League Soccer and with various U.S. national youth teams.
-
C.
Ben Louw
Ben Louw is an individual notable enough to be specifically cited as a prominent bearer of the surname Louw.
-
D.
Jan T. Kleyna
Jan T. Kleyna is an astronomer known for discovering outer irregular moons of Jupiter, including Taygete.
-
E.
Fred J. Koenekamp
Fred J. Koenekamp was an American cinematographer renowned for his work on major films of the 1970s and 1980s, earning an Academy Award and multiple nominations for his visually striking photography.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee3dd80f08190a1704521a764e22c |
completed | March 9, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb1c90648190a76cee07508a83b9 |
completed | March 14, 2026, 6:07 a.m. |
Created at: March 9, 2026, 3:13 p.m.