Triple
T18259772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanche Yurka |
E437317
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Blanche |
—
|
NE NERFINISHED |
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: Blanche | Statement: [Blanche Yurka, givenName, Blanche]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blanche Context triple: [Blanche Yurka, givenName, Blanche]
-
A.
Blanche
Blanche is a Paris Métro station located in the Montmartre area, serving Line 2 near the Moulin Rouge.
-
B.
Blanche
chosen
Blanche is a feminine given name of French origin historically associated with nobility and literary figures.
-
C.
Blanche Hanalis
Blanche Hanalis was an American television writer and producer best known for adapting and developing popular family-oriented series and literary works for TV.
-
D.
Blanche DuBois
Blanche DuBois is the fragile, delusional Southern belle at the center of Tennessee Williams' play "A Streetcar Named Desire," whose psychological unraveling drives the story's tragic arc.
-
E.
Blanche Devereaux
Blanche Devereaux is a flirtatious, glamorous Southern belle and one of the four central housemates in the classic sitcom "The Golden Girls."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd89899c8190b8b652c4f61aa5cf |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:34 a.m.