Triple
T15811147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dick Butkus |
E383355
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Helen Butkus |
E383355
|
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: Helen Butkus | Statement: [Dick Butkus, spouse, Helen Butkus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Butkus Context triple: [Dick Butkus, spouse, Helen Butkus]
-
A.
Helen Butkus
chosen
Helen Butkus is best known as the wife of legendary Chicago Bears Hall of Fame linebacker Dick Butkus.
-
B.
Martine Bancroft
Martine Bancroft is a Marvel Comics character closely associated with the antihero Morbius, often depicted as his fiancée and a key emotional anchor in his storyline.
-
C.
Betty Schaefer
Betty Schaefer is an aspiring young screenwriter who becomes a key romantic and creative foil to Joe Gillis in the classic film noir Sunset Boulevard.
-
D.
Kathy Summerall
Kathy Summerall is known as the wife of legendary American sportscaster and former NFL player Pat Summerall.
-
E.
Laura Ricketts
Laura Ricketts is an American attorney, co-owner of the Chicago Cubs, and prominent LGBTQ+ activist and political donor.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b52aae14819091de08630e7e1d1a |
completed | April 16, 2026, 10:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa131784c8190bd6aba2cca084d20 |
completed | May 9, 2026, 9:03 p.m. |
Created at: April 10, 2026, 4:49 a.m.