Triple
T21760682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riviera |
E537155
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Liza Marshall |
—
|
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: Liza Marshall | Statement: [Riviera, producer, Liza Marshall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liza Marshall Context triple: [Riviera, producer, Liza Marshall]
-
A.
Liza Marshall
chosen
Liza Marshall is a British film and television producer known for her work on projects such as "Before I Go to Sleep" and "Temple."
-
B.
Liza Elliott
Liza Elliott is the conflicted, high-powered fashion magazine editor whose psychoanalytic journey drives the plot of the musical "Lady in the Dark."
-
C.
Liza Todd
Liza Todd is an American sculptor and the daughter of actress Elizabeth Taylor and producer Mike Todd.
-
D.
Liza Cody
Liza Cody is a British crime fiction author best known for her pioneering female private-eye novels, including the Anna Lee series.
-
E.
Liza Miller
Liza Miller is the 40-year-old divorced mother who pretends to be in her twenties to restart her publishing career in the TV series "Younger."
- 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d91e9788190a11d0295306e78a4 |
completed | April 28, 2026, 2:38 a.m. |
Created at: April 16, 2026, 6:50 p.m.