Triple
T7469821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Willis |
E176472
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Helen Willis |
E286870
|
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 Willis | Statement: [Tom Willis, spouse, Helen Willis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Willis Context triple: [Tom Willis, spouse, Helen Willis]
-
A.
Helen Willis
chosen
Helen Willis is a central character on the sitcom "The Jeffersons," known as Louise Jefferson’s close friend and one half of the show’s groundbreaking interracial couple.
-
B.
Helen Wright
Helen Wright is a wealthy, emotionally volatile socialite who becomes romantically entangled with a young violin prodigy in the film "Humoresque."
-
C.
Helen Hughes
Helen Hughes was a daughter of Charles Evans Hughes, the prominent American statesman who served as both U.S. Secretary of State and Chief Justice of the Supreme Court.
-
D.
Helen Marshall
Helen Marshall is a British academic leader and higher education administrator who has served as Vice-Chancellor of the University of Salford.
-
E.
Helen Mack
Helen Mack was an American film and radio actress of the 1930s and 1940s, known for her versatile performances in both comedy and drama.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3f845e081908117783ff1e63e23 |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9494351488190852b600d9666d1eb |
completed | March 29, 2026, 3:46 p.m. |
Created at: March 27, 2026, 3:41 p.m.