Triple
T15275413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beethoven |
E365124
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Nicholle Tom |
E699893
|
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: Nicholle Tom | Statement: [Beethoven, starring, Nicholle Tom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicholle Tom Context triple: [Beethoven, starring, Nicholle Tom]
-
A.
Nicholle Tom
chosen
Nicholle Tom is an American actress best known for her role as Maggie Sheffield on the 1990s sitcom "The Nanny."
-
B.
Tara Lynne O’Neill
Tara Lynne O’Neill is a Northern Irish actress best known for her prominent role in the hit comedy series "Derry Girls."
-
C.
Tiana Silliphant
Tiana Silliphant is known as the wife of Oscar-winning American screenwriter Stirling Silliphant.
-
D.
Julianne Simms
Julianne Simms is a central character in the television series "Breakout Kings," known for her role as a brilliant but troubled analyst who assists U.S. Marshals in tracking down escaped convicts.
-
E.
Heather Tom
Heather Tom is an American actress best known for her long-running roles on daytime soap operas such as "The Young and the Restless," "One Life to Live," and "The Bold and the Beautiful."
- 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_69ff0b39b6f88190ac9d6532e99fda31 |
completed | May 9, 2026, 10:23 a.m. |
Created at: April 10, 2026, 3:14 a.m.