Triple
T3926254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | To Catch a Thief |
E93283
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Frances Stevens |
E213649
|
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: Frances Stevens | Statement: [To Catch a Thief, mainCharacter, Frances Stevens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frances Stevens Context triple: [To Catch a Thief, mainCharacter, Frances Stevens]
-
A.
Frances Stevens
chosen
Frances Stevens is a fictional socialite character best known as Grace Kelly’s witty and glamorous role in Alfred Hitchcock’s 1955 film "To Catch a Thief."
-
B.
Elizabeth Stevens
Elizabeth Stevens is known as the daughter of the late U.S. Supreme Court Justice John Paul Stevens.
-
C.
Carol Stevens
Carol Stevens is best known as one of the former wives of American novelist and journalist Norman Mailer.
-
D.
Anne Wheeler
Anne Wheeler is a fictional trapeze artist and acrobat featured in the musical film "The Greatest Showman."
-
E.
Elizabeth Flanagan
Elizabeth Flanagan was the wife of C. Everett Koop, the prominent U.S. Surgeon General known for his influential public health advocacy.
- 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_69aed96bfa1081908f7b30f2c647dee6 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeed80a1e48190aa39748b9db42701 |
completed | March 9, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c6ed5910819095de0dce09bd50b8 |
completed | March 14, 2026, 8:37 p.m. |
Created at: March 9, 2026, 3:23 p.m.