Triple
T4043701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drop Dead Diva |
E84011
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object |
Grayson Kent
Grayson Kent is a central character in the legal dramedy "Drop Dead Diva," portrayed as a charming and principled attorney who serves as the main love interest of the show's protagonist.
|
E408610
|
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: Grayson Kent | Statement: [Drop Dead Diva, hasMainCharacter, Grayson Kent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grayson Kent Context triple: [Drop Dead Diva, hasMainCharacter, Grayson Kent]
-
A.
Graydon Carter
Graydon Carter is a Canadian-born journalist and longtime editor of Vanity Fair, known for his influential role in media and culture.
-
B.
Grayson Villanueva
Grayson Villanueva is a voice actor and singer known for his work in animated film and television, including contributing vocals to Pixar’s "Turning Red."
-
C.
Grayson
Grayson is an unincorporated community located in Stanislaus County, California.
-
D.
Ashton Moss
Ashton Moss is an area in Greater Manchester, England, known for its retail and leisure park and served by the Manchester Metrolink network.
-
E.
Landon
Landon is a masculine given name most notably associated with American soccer star Landon Donovan.
- 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: Grayson Kent Triple: [Drop Dead Diva, hasMainCharacter, Grayson Kent]
Generated description
Grayson Kent is a central character in the legal dramedy "Drop Dead Diva," portrayed as a charming and principled attorney who serves as the main love interest of the show's protagonist.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grayson Kent Target entity description: Grayson Kent is a central character in the legal dramedy "Drop Dead Diva," portrayed as a charming and principled attorney who serves as the main love interest of the show's protagonist.
-
A.
Graydon Carter
Graydon Carter is a Canadian-born journalist and longtime editor of Vanity Fair, known for his influential role in media and culture.
-
B.
Grayson Villanueva
Grayson Villanueva is a voice actor and singer known for his work in animated film and television, including contributing vocals to Pixar’s "Turning Red."
-
C.
Grayson
Grayson is an unincorporated community located in Stanislaus County, California.
-
D.
Ashton Moss
Ashton Moss is an area in Greater Manchester, England, known for its retail and leisure park and served by the Manchester Metrolink network.
-
E.
Landon
Landon is a masculine given name most notably associated with American soccer star Landon Donovan.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb5d759c8190b61fbbe94ffe2bf7 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5564fb54c81909f40ca1d6f1e521e |
completed | March 14, 2026, 12:36 p.m. |
| NEDg | Description generation | batch_69b5579085608190937528de7e0f987e |
completed | March 14, 2026, 12:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b55828506081908181436282907b08 |
completed | March 14, 2026, 12:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.