Triple
T14853828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shades of Blue |
E349298
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Nina Wass
Nina Wass is a television producer known for her executive work on drama series such as "Shades of Blue."
|
E1124069
|
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: Nina Wass | Statement: [Shades of Blue, executiveProducer, Nina Wass]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nina Wass Context triple: [Shades of Blue, executiveProducer, Nina Wass]
-
A.
Nina Fock
Nina Foch was a Dutch-born American actress and acting teacher known for her roles in classic films such as "An American in Paris," "The Ten Commandments," and "Executive Suite."
-
B.
Nina Stevens
Nina Stevens is the wife of Canadian businessman and former federal cabinet minister Sinclair Stevens.
-
C.
Nina
Nina is a feminine given name used in various cultures, often as a short form of names like Antonina or Giannina, and borne by numerous notable figures in the arts and public life.
-
D.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
-
E.
Nina
Nina is a biographical drama film written and directed by Cynthia Mort that portrays the life and struggles of legendary musician Nina Simone.
- 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: Nina Wass Triple: [Shades of Blue, executiveProducer, Nina Wass]
Generated description
Nina Wass is a television producer known for her executive work on drama series such as "Shades of Blue."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nina Wass Target entity description: Nina Wass is a television producer known for her executive work on drama series such as "Shades of Blue."
-
A.
Nina Fock
Nina Foch was a Dutch-born American actress and acting teacher known for her roles in classic films such as "An American in Paris," "The Ten Commandments," and "Executive Suite."
-
B.
Nina Stevens
Nina Stevens is the wife of Canadian businessman and former federal cabinet minister Sinclair Stevens.
-
C.
Nina
Nina is a feminine given name used in various cultures, often as a short form of names like Antonina or Giannina, and borne by numerous notable figures in the arts and public life.
-
D.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
-
E.
Nina
Nina is a biographical drama film written and directed by Cynthia Mort that portrays the life and struggles of legendary musician Nina Simone.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44318f0819080b6c599f2d3474f |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6506ace48190819504b93f575660 |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe66a5f3a88190827c6c9247323153 |
completed | May 8, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6736ff34819098524e4401a414aa |
completed | May 8, 2026, 10:44 p.m. |
Created at: April 10, 2026, 1:54 a.m.