Triple
T4979615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stonewall Book Award |
E111850
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object |
Mike Morgan
Mike Morgan is a benefactor known for sponsoring the Stonewall Book Award, which honors outstanding LGBTQ+ literature.
|
E486534
|
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: Mike Morgan | Statement: [Stonewall Book Award, sponsor, Mike Morgan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Morgan Context triple: [Stonewall Book Award, sponsor, Mike Morgan]
-
A.
Brian Routh
Brian Routh was a British performance artist and musician best known as one half of the avant-garde comedy and performance duo The Kipper Kids.
-
B.
Brian Mahoney
Brian Mahoney is an actor best known for his role in the cult crime film "The Boondock Saints."
-
C.
Mike Gaffey
Mike Gaffey is a songwriter best known for co-writing the track "RITMO (Bad Boys for Life)."
-
D.
Michael Maloney
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
-
E.
Michael Potts
Michael Potts is an American actor known for his work in film, television, and theater, including notable roles in projects like "The Wire," "True Detective," and various Broadway productions.
- 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: Mike Morgan Triple: [Stonewall Book Award, sponsor, Mike Morgan]
Generated description
Mike Morgan is a benefactor known for sponsoring the Stonewall Book Award, which honors outstanding LGBTQ+ literature.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mike Morgan Target entity description: Mike Morgan is a benefactor known for sponsoring the Stonewall Book Award, which honors outstanding LGBTQ+ literature.
-
A.
Brian Routh
Brian Routh was a British performance artist and musician best known as one half of the avant-garde comedy and performance duo The Kipper Kids.
-
B.
Brian Mahoney
Brian Mahoney is an actor best known for his role in the cult crime film "The Boondock Saints."
-
C.
Mike Gaffey
Mike Gaffey is a songwriter best known for co-writing the track "RITMO (Bad Boys for Life)."
-
D.
Michael Maloney
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
-
E.
Michael Potts
Michael Potts is an American actor known for his work in film, television, and theater, including notable roles in projects like "The Wire," "True Detective," and various Broadway productions.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd723418e881908f1e43b1be0a2f17 |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be924befc08190a077adca99fb4b86 |
completed | March 21, 2026, 12:42 p.m. |
| NEDg | Description generation | batch_69be942dac9c8190a5861ca0aaa44c90 |
completed | March 21, 2026, 12:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be94a7e15481908f17feafb593b97b |
completed | March 21, 2026, 12:52 p.m. |
Created at: March 20, 2026, 1:33 p.m.