Triple
T15275415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beethoven |
E365124
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Sarah Rose Karr |
E956135
|
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: Sarah Rose Karr | Statement: [Beethoven, starring, Sarah Rose Karr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Rose Karr Context triple: [Beethoven, starring, Sarah Rose Karr]
-
A.
Sarah Rose Karr
chosen
Sarah Rose Karr is an American former child actress best known for her role in the family film "Beethoven's 2nd" and appearances in early 1990s movies.
-
B.
Lauren Groff
Lauren Groff is an acclaimed contemporary American novelist and short story writer known for works such as "Fates and Furies," "Matrix," and "Florida."
-
C.
Sara Quin
Sara Quin is a Canadian musician best known as one half of the indie pop duo Tegan and Sara.
-
D.
Lorrie Moore
Lorrie Moore is an acclaimed American fiction writer best known for her witty, emotionally incisive short stories and novels such as "Birds of America" and "Who Will Run the Frog Hospital?".
-
E.
Amy Hempel
Amy Hempel is an American short story writer renowned for her minimalist style, emotional precision, and influential contributions to contemporary fiction.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00952731c8190bf6a5e6e10c95b94 |
completed | April 15, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee608217881909c9f7f7c753cf0a8 |
completed | May 9, 2026, 7:45 a.m. |
Created at: April 10, 2026, 3:14 a.m.