Triple
T10811317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claude Rains |
E255104
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Isabel Jeans |
E255106
|
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: Isabel Jeans | Statement: [Claude Rains, spouse, Isabel Jeans]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isabel Jeans Context triple: [Claude Rains, spouse, Isabel Jeans]
-
A.
Isabel Jeans
chosen
Isabel Jeans was a British stage and film actress known for her sophisticated roles in early 20th-century cinema, including appearances in several Alfred Hitchcock films.
-
B.
Ursula Jeans
Ursula Jeans was a British stage and film actress known for her versatile character roles in mid-20th-century cinema and theatre.
-
C.
Sasson Jeans
Sasson Jeans was a popular American denim and sportswear brand that gained prominence in the late 1970s and 1980s for its fashion-forward jeans and memorable advertising campaigns.
-
D.
Paige Denim
Paige Denim is a premium Los Angeles–based fashion brand best known for its high-quality designer jeans and contemporary denim apparel.
-
E.
Pepe Jeans
Pepe Jeans is a British denim and casualwear fashion brand known for its trendy jeans and youthful, urban style.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733b7bfac8190b6ae34144376d6ad |
completed | April 9, 2026, 5:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de853692f08190914cbeaf1a558730 |
completed | April 14, 2026, 6:19 p.m. |
Created at: April 8, 2026, 9:18 p.m.