Triple
T16441235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Sanders |
E399306
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Janet Sosna |
—
|
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: Janet Sosna | Statement: [Steve Sanders, spouse, Janet Sosna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Janet Sosna Context triple: [Steve Sanders, spouse, Janet Sosna]
-
A.
Janet Sosna
chosen
Janet Sosna is a character from the television series "Beverly Hills, 90210," known for her relationship with Steve Sanders and her role as a journalist.
-
B.
Janet Margolin
Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
-
C.
Barbara Siegel
Barbara Siegel is an American author best known for co-writing numerous science fiction and fantasy novels and game-related books, often in collaboration with her husband Scott Siegel.
-
D.
Judy Levitt
Judy Levitt is an American actress best known for her long marriage to Star Trek actor Walter Koenig and for appearing in several of his film and television projects.
-
E.
Diane Nabatoff
Diane Nabatoff is a film and television producer known for her work on crime dramas and character-driven stories.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ba7fb0c8190a6a872705cd38987 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:10 a.m.