Triple
T17623679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood Wives |
E429773
|
entity |
| Predicate | starred |
P5563
|
FINISHED |
| Object | Mary Crosby |
—
|
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: Mary Crosby | Statement: [Hollywood Wives, starred, Mary Crosby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Crosby Context triple: [Hollywood Wives, starred, Mary Crosby]
-
A.
Mary Crosby
chosen
Mary Crosby is an American actress best known for her role as Kristin Shepard on the television series "Dallas."
-
B.
Mary Elfrieda Scruggs
Mary Elfrieda Scruggs, better known as Mary Lou Williams, was an influential American jazz pianist, composer, and arranger whose career spanned swing, bebop, and beyond.
-
C.
Melba Snyder
Melba Snyder is a character associated with the animated television series "Zip."
-
D.
Mary Birdsong
Mary Birdsong is an American actress and comedian known for her character work in film, television, and voice acting.
-
E.
Mary Cunningham
Mary Cunningham is known as the spouse of Welsh actor Clive Merrison, recognized for his extensive work in British television, film, and radio drama.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dba664c81909dcaf44779db5565 |
completed | April 19, 2026, 5:52 a.m. |
Created at: April 10, 2026, 5:52 a.m.