Triple
T3994678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blansky's Beauties |
E87071
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Nancy Blansky
Nancy Blansky is the central character of the 1970s American sitcom "Blansky's Beauties," portrayed as a seasoned Las Vegas showbiz professional managing a troupe of young performers.
|
E621285
|
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: Nancy Blansky | Statement: [Blansky's Beauties, mainCharacter, Nancy Blansky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nancy Blansky Context triple: [Blansky's Beauties, mainCharacter, Nancy Blansky]
-
A.
Nancy Schafer
Nancy Schafer is a film and television producer known for her work on independent and documentary projects.
-
B.
Nancy Gross
Nancy Gross was the wife of renowned American film director Howard Hawks.
-
C.
Nancy Kovack
Nancy Kovack is an American actress best known for her film and television roles in the 1960s, including appearances in "Jason and the Argonauts" and various popular TV series.
-
D.
Nancy Kruse
Nancy Kruse is a writer known for her work on the story of the animated film "Encanto."
-
E.
Nancy Morris
Nancy Morris was the wife of American politician and U.S. Representative Henry Winter Davis, a prominent figure in Maryland politics during the mid-19th century.
- 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: Nancy Blansky Triple: [Blansky's Beauties, mainCharacter, Nancy Blansky]
Generated description
Nancy Blansky is the central character of the 1970s American sitcom "Blansky's Beauties," portrayed as a seasoned Las Vegas showbiz professional managing a troupe of young performers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nancy Blansky Target entity description: Nancy Blansky is the central character of the 1970s American sitcom "Blansky's Beauties," portrayed as a seasoned Las Vegas showbiz professional managing a troupe of young performers.
-
A.
Nancy Schafer
Nancy Schafer is a film and television producer known for her work on independent and documentary projects.
-
B.
Nancy Gross
Nancy Gross was the wife of renowned American film director Howard Hawks.
-
C.
Nancy Kovack
Nancy Kovack is an American actress best known for her film and television roles in the 1960s, including appearances in "Jason and the Argonauts" and various popular TV series.
-
D.
Nancy Kruse
Nancy Kruse is a writer known for her work on the story of the animated film "Encanto."
-
E.
Nancy Morris
Nancy Morris was the wife of American politician and U.S. Representative Henry Winter Davis, a prominent figure in Maryland politics during the mid-19th century.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa1f0fb88190aafbfdc98bc8652d |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7239e1ea481908c64d8a2d600aa30 |
completed | March 28, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_69c724d740588190a4ed1aa532ee7335 |
completed | March 28, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c725aedfd0819097ae603cc49ff9a8 |
completed | March 28, 2026, 12:49 a.m. |
Created at: March 9, 2026, 3:34 p.m.