Triple
T2753659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Snyder |
E61047
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Tanya Snyder |
E187141
|
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: Tanya Snyder | Statement: [Dan Snyder, spouse, Tanya Snyder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tanya Snyder Context triple: [Dan Snyder, spouse, Tanya Snyder]
-
A.
Tanya Snyder
chosen
Tanya Snyder is an American businesswoman and philanthropist best known as the co-owner and former co-CEO of the Washington Commanders NFL franchise.
-
B.
Deborah Snyder
Deborah Snyder is an American film producer known for her work on major superhero and genre films, particularly through her collaborations with director Zack Snyder on projects within the DC Extended Universe.
-
C.
Colleen Sostorics
Colleen Sostorics is a Canadian former ice hockey defenceman and three-time Olympic gold medallist who starred with the national women’s team.
-
D.
Nina Sutter
Nina Sutter is a notable individual who carries the Sutter surname, recognized as one of its distinguished bearers.
-
E.
Lori Collins
Lori Collins is a central character in the comedy film "Ted," known as John Bennett’s long-suffering girlfriend who pushes him to grow up and choose between her and his crude, living teddy bear best friend.
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb6ed9c08190824d1866e198ef80 |
completed | March 7, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f0432e081908110ede1c2b7a54a |
completed | March 14, 2026, 3:30 p.m. |
Created at: March 6, 2026, 9:56 p.m.