Triple
T9753829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Vowell |
E236504
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Amy Vowell |
E818960
|
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: Amy Vowell | Statement: [Sarah Vowell, sibling, Amy Vowell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amy Vowell Context triple: [Sarah Vowell, sibling, Amy Vowell]
-
A.
Amy Vowell
chosen
Amy Vowell is the twin sister of American author and humorist Sarah Vowell, known primarily in relation to her sibling’s public profile.
-
B.
Ariel Truax
Ariel Truax is a central love interest and spirited newcomer in the comedy film "Grumpy Old Men," whose arrival stirs up rivalry and romance between the two elderly protagonists.
-
C.
Libby Snyder
Libby Snyder is known as the spouse of American poet James Wright.
-
D.
Amy Skinner
Amy Skinner is known as the wife of renowned American rock climber and mountaineer Todd Skinner.
-
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 (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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9fb01ad08190b2435fa505c622bc |
completed | April 1, 2026, 10:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcd60e1c81908ea2e38ca91e58f6 |
completed | April 5, 2026, 1:37 a.m. |
Created at: March 30, 2026, 8:24 p.m.