Triple
T3878062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William James Murray |
E92551
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jennifer Butler |
E83907
|
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: Jennifer Butler | Statement: [William James Murray, spouse, Jennifer Butler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jennifer Butler Context triple: [William James Murray, spouse, Jennifer Butler]
-
A.
Jennifer Butler
chosen
Jennifer Butler was an American costume designer best known for her long-term relationship and marriage to actor Bill Murray.
-
B.
Joanne Tucker
Joanne Tucker is an American actress known for her work in independent films and theater, as well as for her involvement in arts-focused nonprofit initiatives.
-
C.
Valerie Curtin
Valerie Curtin is an American actress and screenwriter known for her work in film and television, including co-writing the acclaimed legal drama "...And Justice for All."
-
D.
Linda Spalding
Linda Spalding is a Canadian-American writer and editor known for her award-winning fiction and non-fiction, including works that explore history, identity, and moral complexity.
-
E.
Ann Buck
Ann Buck is known as the former wife of American sportscaster Joe Buck.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec72fa7c81909c73b3cf90597e9a |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b52845684c8190b6f0676319a6fc3c |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:20 p.m.