Triple
T17917634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cristina Raines |
E447973
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Cristina Raines |
—
|
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: Cristina Raines | Statement: [Cristina Raines, name, Cristina Raines]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cristina Raines Context triple: [Cristina Raines, name, Cristina Raines]
-
A.
Cristina Raines
chosen
Cristina Raines is an American actress best known for her roles in 1970s and 1980s film and television, including prominent performances in horror and drama projects.
-
B.
Laura Rister
Laura Rister is a film producer and executive known for her work on independent and prestige projects, including the financial thriller "Margin Call."
-
C.
Maria Clements
Maria Clements was the wife of American film and television actor Stanley Clements.
-
D.
Kristin Squires
Kristin Squires is an individual known primarily in relation to Dr. Jeffrey Squires, with whom she has a personal connection.
-
E.
Kristin Burr
Kristin Burr is a film producer known for her work on major studio projects, including Disney live-action adaptations such as "Cruella."
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30778fc81908b5b2e308fb158a5 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 10:20 a.m.