Triple
T1379263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Code of the Woosters |
E29298
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Madeline Bassett |
E210289
|
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: Madeline Bassett | Statement: [The Code of the Woosters, character, Madeline Bassett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madeline Bassett Context triple: [The Code of the Woosters, character, Madeline Bassett]
-
A.
Madeline Bassett
chosen
Madeline Bassett is a dreamy, sentimental young woman in P. G. Wodehouse’s Jeeves and Wooster stories, often entangled in unwanted romantic misunderstandings with Bertie Wooster.
-
B.
Ruby Aldridge
Ruby Aldridge is an American fashion model known for her runway and editorial work with major designers and magazines.
-
C.
Valarie Pettiford
Valarie Pettiford is an American actress, singer, and dancer known for her work on stage, television, and film, including roles in productions such as the musical "Fosse" and the TV series "Half & Half."
-
D.
Marianne Stewart
Marianne Stewart was an American actress active in mid-20th-century film, television, and theater.
-
E.
Vondie Curtis-Hall
Vondie Curtis-Hall is an American actor and filmmaker known for his work in film and television, both in front of and behind the camera.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3187f248190a5813274b0ef944d |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb8a58ec81908b2bb5c27283bafa |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 1, 2026, 7:59 p.m.