Triple
T428727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rip Van Winkle |
E9666
|
entity |
| Predicate | containsCharacter |
P5716
|
FINISHED |
| Object |
Dame Van Winkle
Dame Van Winkle is the nagging, overbearing wife of the title character in Washington Irving’s short story "Rip Van Winkle."
|
E55293
|
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: Dame Van Winkle | Statement: [Rip Van Winkle, containsCharacter, Dame Van Winkle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dame Van Winkle Context triple: [Rip Van Winkle, containsCharacter, Dame Van Winkle]
-
A.
Elizabeth Eldridge
Elizabeth Eldridge was the wife of Salem Village minister Samuel Parris, associated with the period of the Salem witch trials in late 17th-century Massachusetts.
-
B.
Doris
Doris is an Oceanid from Greek mythology, known as the wife of the sea god Nereus and mother of the Nereids.
-
C.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
D.
Nance
Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
-
E.
Mrs. Soffel
Mrs. Soffel is a 1984 American period crime drama film starring Diane Keaton and Mel Gibson, based on the true story of a warden’s wife who helps two convicted murderers escape from a Pittsburgh prison.
- 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: Dame Van Winkle Triple: [Rip Van Winkle, containsCharacter, Dame Van Winkle]
Generated description
Dame Van Winkle is the nagging, overbearing wife of the title character in Washington Irving’s short story "Rip Van Winkle."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dame Van Winkle Target entity description: Dame Van Winkle is the nagging, overbearing wife of the title character in Washington Irving’s short story "Rip Van Winkle."
-
A.
Elizabeth Eldridge
Elizabeth Eldridge was the wife of Salem Village minister Samuel Parris, associated with the period of the Salem witch trials in late 17th-century Massachusetts.
-
B.
Doris
Doris is an Oceanid from Greek mythology, known as the wife of the sea god Nereus and mother of the Nereids.
-
C.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
D.
Nance
Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
-
E.
Mrs. Soffel
Mrs. Soffel is a 1984 American period crime drama film starring Diane Keaton and Mel Gibson, based on the true story of a warden’s wife who helps two convicted murderers escape from a Pittsburgh prison.
- F. None of above. chosen
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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eeecb64c81908c5c83ef7c0181e6 |
completed | Feb. 28, 2026, 1:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4366960dc81908708bd168aa3a278 |
completed | March 1, 2026, 12:51 p.m. |
| NEDg | Description generation | batch_69a436c6f1a0819086f8d8f12bc82e87 |
completed | March 1, 2026, 12:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4379eee248190a417b81afbb403ae |
completed | March 1, 2026, 12:57 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.