Triple
T14580101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lily Rabe |
E342168
|
entity |
| Predicate | notableRole |
P22
|
FINISHED |
| Object | Nora Montgomery |
E327881
|
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 Montgomery | Statement: [Lily Rabe, notableRole, Nora Montgomery]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nora Montgomery Context triple: [Lily Rabe, notableRole, Nora Montgomery]
-
A.
Nora Montgomery
chosen
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.
-
B.
Nora Hayden
Nora Hayden was an American actress and model active in the mid-20th century, known for her roles in film and television.
-
C.
Helen Montgomery
Helen Montgomery is a science fiction fan and convention organizer known for her editorial work on the fanzine Journey Planet.
-
D.
Nora Prentiss
Nora Prentiss is a 1947 film noir drama centered on a nightclub singer whose affair with a married doctor leads to deception and tragedy.
-
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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f6f78c81908a30ecb4c025299d |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bbfc6048190897f064a5686ebf8 |
completed | May 9, 2026, 1:19 a.m. |
Created at: April 10, 2026, 1:24 a.m.