Triple
T19455606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghosts of Mars |
E486724
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Joanna Cassidy |
—
|
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: Joanna Cassidy | Statement: [Ghosts of Mars, starring, Joanna Cassidy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joanna Cassidy Context triple: [Ghosts of Mars, starring, Joanna Cassidy]
-
A.
Joanna Cassidy
chosen
Joanna Cassidy is an American actress best known for her roles in films like Blade Runner and Who Framed Roger Rabbit, as well as numerous television appearances.
-
B.
Joanna Miles
Joanna Miles is an American actress best known for her work in film, television, and stage productions, including roles in adaptations of classic literary and theatrical works.
-
C.
Laura Davenport
Laura Davenport is the daughter of English actor Nigel Davenport.
-
D.
Raquel Cassidy
Raquel Cassidy is a British actress known for her roles in television series such as Downton Abbey and Lead Balloon.
-
E.
Lisa Conroy
Lisa Conroy is the hardworking, empathetic general manager of a roadside sports bar who struggles to protect and support her staff amid personal and professional turmoil in the film "Support the Girls."
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c2b1108190b492ca23487b91f8 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:38 p.m.