Triple
T4637161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilella Cather |
E101560
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Wilella
Wilella is the given first name of the American novelist Willa Cather, known for her classic works about frontier life on the Great Plains.
|
E101560
|
NE FINISHED |
How this triple was built (4 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: Wilella | Statement: [Wilella Cather, givenName, Wilella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilella Context triple: [Wilella Cather, givenName, Wilella]
-
A.
Wilella
Wilella is the full given name of American novelist Willa Cather, renowned for her works depicting frontier life on the Great Plains.
-
B.
Sheilia
Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
-
C.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
-
D.
Lela
Lela is a feminine given name used in various cultures, often as a variant of Leila or Layla.
-
E.
Verna
Verna is a feminine given name that gained particular recognition through film editor Verna Fields, known for her work on movies like "Jaws."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wilella Triple: [Wilella Cather, givenName, Wilella]
Generated description
Wilella is the given first name of the American novelist Willa Cather, known for her classic works about frontier life on the Great Plains.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wilella Target entity description: Wilella is the given first name of the American novelist Willa Cather, known for her classic works about frontier life on the Great Plains.
-
A.
Wilella
chosen
Wilella is the full given name of American novelist Willa Cather, renowned for her works depicting frontier life on the Great Plains.
-
B.
Sheilia
Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
-
C.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
-
D.
Lela
Lela is a feminine given name used in various cultures, often as a variant of Leila or Layla.
-
E.
Verna
Verna is a feminine given name that gained particular recognition through film editor Verna Fields, known for her work on movies like "Jaws."
- F. None of above.
Provenance (5 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a62a9e48190b0cf1cbcc51f00c0 |
completed | March 20, 2026, 2:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfacba5fc8190bc86157ee5719ced |
completed | March 21, 2026, 1:56 a.m. |
| NEDg | Description generation | batch_69bdfed8a8b48190bcb98e2ff1886b65 |
completed | March 21, 2026, 2:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdff9ff3748190af5e5a6d91976abc |
completed | March 21, 2026, 2:17 a.m. |
Created at: March 20, 2026, 1:13 p.m.