Triple
T13792493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harlem (TV series) |
E331432
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Tyler Lepley
Tyler Lepley is an American actor best known for his roles in television dramas and comedies, including prominent parts on shows like "Harlem" and "The Haves and the Have Nots."
|
E1066421
|
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: Tyler Lepley | Statement: [Harlem (TV series), castMember, Tyler Lepley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tyler Lepley Context triple: [Harlem (TV series), castMember, Tyler Lepley]
-
A.
Chris Leal
Chris Leal is a musician best known for having been an early member of the American rock band No Doubt.
-
B.
Matthew Kellard
Matthew Kellard is a screenwriter known for his work on the film "Night School."
-
C.
Dane Coles
Dane Coles is a New Zealand rugby union hooker renowned for his dynamic play for the All Blacks and long-standing impact in Super Rugby.
-
D.
Matthew Skemp
Matthew Skemp is a musician best known as a member of the experimental indie rock band Volcano Choir.
-
E.
Mike Eley
Mike Eley is a British cinematographer known for his work on acclaimed films and television dramas.
- 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: Tyler Lepley Triple: [Harlem (TV series), castMember, Tyler Lepley]
Generated description
Tyler Lepley is an American actor best known for his roles in television dramas and comedies, including prominent parts on shows like "Harlem" and "The Haves and the Have Nots."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tyler Lepley Target entity description: Tyler Lepley is an American actor best known for his roles in television dramas and comedies, including prominent parts on shows like "Harlem" and "The Haves and the Have Nots."
-
A.
Chris Leal
Chris Leal is a musician best known for having been an early member of the American rock band No Doubt.
-
B.
Matthew Kellard
Matthew Kellard is a screenwriter known for his work on the film "Night School."
-
C.
Dane Coles
Dane Coles is a New Zealand rugby union hooker renowned for his dynamic play for the All Blacks and long-standing impact in Super Rugby.
-
D.
Matthew Skemp
Matthew Skemp is a musician best known as a member of the experimental indie rock band Volcano Choir.
-
E.
Mike Eley
Mike Eley is a British cinematographer known for his work on acclaimed films and television dramas.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0258a1408190a837d17c6d6a2bd4 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0e3642481908a9b84d8d71fb4d4 |
completed | May 3, 2026, 9:40 p.m. |
| NEDg | Description generation | batch_69f7c1e73fb481909f89ab3c0e9fb7d0 |
completed | May 3, 2026, 9:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c33c2f34819084502d5f03f09ddd |
completed | May 3, 2026, 9:50 p.m. |
Created at: April 9, 2026, 10:11 p.m.