Triple
T12436606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pride |
E297158
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Faye Marsay
Faye Marsay is an English actress known for her roles in film and television, including appearances in "Game of Thrones," "Black Mirror," and "Pride."
|
E983696
|
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: Faye Marsay | Statement: [Pride, stars, Faye Marsay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faye Marsay Context triple: [Pride, stars, Faye Marsay]
-
A.
Isla Smith
Isla Smith is a small island located off the coast of Bahía de los Ángeles in the Gulf of California, Mexico.
-
B.
Molly Farren
Molly Farren is a tragic minor character in George Eliot’s novel "Silas Marner," known as the opium-addicted first wife of Godfrey Cass and the biological mother of Eppie.
-
C.
Emily Firth
Emily Firth is the daughter of Canadian-American actress and novelist Meg Tilly.
-
D.
Kirsty Dillon
Kirsty Dillon is a British actress known for her work in film and television, including roles in dramas and crime series.
-
E.
Heather Sutherland
Heather Sutherland is an Australian academic and historian, best known as the long-term partner of British actress Miriam Margolyes.
- 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: Faye Marsay Triple: [Pride, stars, Faye Marsay]
Generated description
Faye Marsay is an English actress known for her roles in film and television, including appearances in "Game of Thrones," "Black Mirror," and "Pride."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Faye Marsay Target entity description: Faye Marsay is an English actress known for her roles in film and television, including appearances in "Game of Thrones," "Black Mirror," and "Pride."
-
A.
Isla Smith
Isla Smith is a small island located off the coast of Bahía de los Ángeles in the Gulf of California, Mexico.
-
B.
Molly Farren
Molly Farren is a tragic minor character in George Eliot’s novel "Silas Marner," known as the opium-addicted first wife of Godfrey Cass and the biological mother of Eppie.
-
C.
Emily Firth
Emily Firth is the daughter of Canadian-American actress and novelist Meg Tilly.
-
D.
Kirsty Dillon
Kirsty Dillon is a British actress known for her work in film and television, including roles in dramas and crime series.
-
E.
Heather Sutherland
Heather Sutherland is an Australian academic and historian, best known as the long-term partner of British actress Miriam Margolyes.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d8c8fd481909b35ac504127a1b6 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f06d16481909ed2eb5195ebd7e4 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f6400fe9888190ae8244ccc8e8bc39 |
completed | May 2, 2026, 6:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64168d23881908daee7d7cba2160d |
completed | May 2, 2026, 6:24 p.m. |
Created at: April 8, 2026, 9:55 p.m.