Triple
T16330012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Ridgely |
E396525
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Nora Prentiss |
E1060181
|
NE FINISHED |
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: Nora Prentiss | Statement: [John Ridgely, notableWork, Nora Prentiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nora Prentiss Context triple: [John Ridgely, notableWork, Nora Prentiss]
-
A.
Nora Prentiss
chosen
Nora Prentiss is a 1947 film noir drama centered on a nightclub singer whose affair with a married doctor leads to deception and tragedy.
-
B.
Amy Prentiss
Amy Prentiss is a 1970s American television crime drama series featuring Jessica Walter as a pioneering female chief of detectives in San Francisco.
-
C.
Ann Prentiss
Ann Prentiss was an American character actress known for her supporting roles in film and television during the 1960s and 1970s.
-
D.
Nora Montgomery
Nora Montgomery is a tragic, ghostly character from the television series "American Horror Story: Murder House," known for her role as a grief-stricken 1920s socialite and wife of mad surgeon Charles Montgomery.
-
E.
Nora Manning
Nora Manning is a minor supporting character in the romantic comedy-drama film "As Good as It Gets."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4debef08190a64f13214bfa098f |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c4ca7ac819098cae8aabfe7e395 |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:07 a.m.