Triple
T15516324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talia Schwikert |
E368842
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Talia Schwikert |
—
|
NE NERFINISHED |
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: Talia Schwikert | Statement: [Talia Schwikert, name, Talia Schwikert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talia Schwikert Context triple: [Talia Schwikert, name, Talia Schwikert]
-
A.
Talia (Tasha) Schwikert
chosen
Talia (Tasha) Schwikert is an American former artistic gymnast, 2000 Olympian, and multiple-time national champion who later competed collegiately for UCLA.
-
B.
Kayla Alpert
Kayla Alpert is a television writer and producer known for her work on series such as the Netflix show "Wednesday."
-
C.
Libby Snyder
Libby Snyder is known as the spouse of American poet James Wright.
-
D.
Rebecca Heineman
Rebecca Heineman is an American video game programmer and designer recognized as one of the industry’s earliest champions and a co-founder of several influential game companies.
-
E.
Libby Geist
Libby Geist is an American documentary film producer best known for her work on acclaimed sports and social-issue documentaries, including the Oscar-winning "O.J.: Made in America."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04033303c8190a87b6384f68a6921 |
completed | April 16, 2026, 1:49 a.m. |
Created at: April 10, 2026, 4:02 a.m.