Triple
T3201618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elia Kazan |
E67063
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Frances Rudge |
E180384
|
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 Rudge | Statement: [Elia Kazan, spouse, Frances Rudge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frances Rudge Context triple: [Elia Kazan, spouse, Frances Rudge]
-
A.
Frances Rudge
chosen
Frances Rudge was the wife of influential American film and theatre director Elia Kazan.
-
B.
Frances Penney
Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
-
C.
Margaret Gamage
Margaret Gamage was a 16th-century Welsh noblewoman of the Gamage family who became Countess of Nottingham through her marriage into the English Howard dynasty.
-
D.
Mary Pugh
Mary Pugh is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Pugh.
-
E.
Helen Morris
Helen Morris is an American book editor and the longtime wife of acclaimed film director Martin Scorsese.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9b046c8819087c0a61c4f9adeb7 |
completed | March 8, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f070d6081909bc6ae1ce127c3d7 |
completed | March 14, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:07 p.m.