Triple
T14351557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cagney & Lacey |
E355864
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Mary Beth Lacey
Mary Beth Lacey is a dedicated, streetwise New York City police detective and working mother from the television series "Cagney & Lacey."
|
E1257444
|
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: Mary Beth Lacey | Statement: [Cagney & Lacey, mainCharacter, Mary Beth Lacey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Beth Lacey Context triple: [Cagney & Lacey, mainCharacter, Mary Beth Lacey]
-
A.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
-
B.
Mary Beth Johnson
Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
-
C.
Mary Beth Peil
Mary Beth Peil is an American actress and singer known for her work on Broadway, in film and television, and for originating prominent roles in major stage productions.
-
D.
Mary Leddy
Mary Leddy was the wife of American labor union official and alleged mob hitman Frank Sheeran, whose life inspired the film "The Irishman."
-
E.
Linda Stokes
Linda Stokes is an American costume designer best known for her long-term marriage to actor James Caan.
- 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: Mary Beth Lacey Triple: [Cagney & Lacey, mainCharacter, Mary Beth Lacey]
Generated description
Mary Beth Lacey is a dedicated, streetwise New York City police detective and working mother from the television series "Cagney & Lacey."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Beth Lacey Target entity description: Mary Beth Lacey is a dedicated, streetwise New York City police detective and working mother from the television series "Cagney & Lacey."
-
A.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
-
B.
Mary Beth Johnson
Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
-
C.
Mary Beth Peil
Mary Beth Peil is an American actress and singer known for her work on Broadway, in film and television, and for originating prominent roles in major stage productions.
-
D.
Mary Leddy
Mary Leddy was the wife of American labor union official and alleged mob hitman Frank Sheeran, whose life inspired the film "The Irishman."
-
E.
Linda Stokes
Linda Stokes is an American costume designer best known for her long-term marriage to actor James Caan.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f4e1e588190bdc7aaf7a2819948 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0167369d9481909015c34d475fac14 |
completed | May 11, 2026, 5:20 a.m. |
| NEDg | Description generation | batch_6a0169aeaa248190b955490c62b763a1 |
completed | May 11, 2026, 5:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a016a103ec0819083dd6cf5af5a20ee |
completed | May 11, 2026, 5:33 a.m. |
Created at: April 10, 2026, 1:14 a.m.