Triple
T1129561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funny Girl |
E24796
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Fanny Brice |
E117113
|
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: Fanny Brice | Statement: [Funny Girl, character, Fanny Brice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fanny Brice Context triple: [Funny Girl, character, Fanny Brice]
-
A.
Fanny Brice
chosen
Fanny Brice was an American comedienne, singer, and actress best known as a star of the Ziegfeld Follies and the inspiration for the musical "Funny Girl."
-
B.
Sophie Tucker
Sophie Tucker was a popular early 20th-century American singer, comedian, and vaudeville star known as "The Last of the Red Hot Mamas."
-
C.
Gertrude Berg
Gertrude Berg was an American actress, screenwriter, and producer best known as the creator and star of the pioneering radio and television series "The Goldbergs."
-
D.
Ruth Etting
Ruth Etting was a popular American singer and actress of the 1920s and 1930s, famed for hits like "Love Me or Leave Me" and known as one of the era's leading torch singers.
-
E.
Gypsy Rose Lee
Gypsy Rose Lee was a famous American burlesque entertainer and author whose life inspired the musical "Gypsy."
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bbf979108190adad7073c8275dd2 |
completed | March 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6f11a31481909e11a01b12841b3d |
completed | March 7, 2026, 6:31 p.m. |
Created at: March 1, 2026, 7:44 p.m.