Triple
T7425441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Wright |
E171355
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Libby Snyder |
E688984
|
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: Libby Snyder | Statement: [James Wright, hasRelative, Libby Snyder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Libby Snyder Context triple: [James Wright, hasRelative, Libby Snyder]
-
A.
Libby Snyder
chosen
Libby Snyder is known as the spouse of American poet James Wright.
-
B.
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."
-
C.
Libby Leist
Libby Leist is a television news executive best known for her leadership role as an executive producer at NBC’s "Today" show.
-
D.
Autumn Snyder
Autumn Snyder was the late daughter of filmmaker Zack Snyder, remembered for her aspiring writing career and the profound impact her death had on her father's life and work.
-
E.
Annalee Whitmore
Annalee Whitmore is a screenwriter known for her work on the classic musical film "Babes in Arms."
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f303eb988190ba9df7946fce1c86 |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8f2ffec108190ab60b0777d97dd89 |
completed | March 29, 2026, 9:38 a.m. |
Created at: March 27, 2026, 3:12 p.m.