Triple
T3154411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selah |
E65949
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Michael Suski
Michael Suski is a writer known for his work associated with the musical project Selah.
|
E331492
|
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: Michael Suski | Statement: [Selah, writer, Michael Suski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Suski Context triple: [Selah, writer, Michael Suski]
-
A.
Brett Veach
Brett Veach is an American football executive best known for building multiple Super Bowl–winning rosters as the general manager of the Kansas City Chiefs.
-
B.
Joshua Bowman
Joshua Bowman is a British actor best known for his role as Daniel Grayson on the television drama series "Revenge."
-
C.
Lance Leipold
Lance Leipold is an American college football coach known for successfully rebuilding programs, most notably turning around the University of Kansas Jayhawks football team after winning multiple Division III national titles at Wisconsin–Whitewater.
-
D.
John Hoberg
John Hoberg is an American television and film writer known for his work on animated and live-action projects, including co-writing the Pixar film "Elemental."
-
E.
Jeff Nickell
Jeff Nickell is an individual notable enough to be specifically referenced as a bearer of the surname Nickell.
- 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: Michael Suski Triple: [Selah, writer, Michael Suski]
Generated description
Michael Suski is a writer known for his work associated with the musical project Selah.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Suski Target entity description: Michael Suski is a writer known for his work associated with the musical project Selah.
-
A.
Brett Veach
Brett Veach is an American football executive best known for building multiple Super Bowl–winning rosters as the general manager of the Kansas City Chiefs.
-
B.
Joshua Bowman
Joshua Bowman is a British actor best known for his role as Daniel Grayson on the television drama series "Revenge."
-
C.
Lance Leipold
Lance Leipold is an American college football coach known for successfully rebuilding programs, most notably turning around the University of Kansas Jayhawks football team after winning multiple Division III national titles at Wisconsin–Whitewater.
-
D.
John Hoberg
John Hoberg is an American television and film writer known for his work on animated and live-action projects, including co-writing the Pixar film "Elemental."
-
E.
Jeff Nickell
Jeff Nickell is an individual notable enough to be specifically referenced as a bearer of the surname Nickell.
- 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5e7f4688190b477186254f8a572 |
completed | March 8, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b22503ba208190814ab2bfbe380c42 |
completed | March 12, 2026, 2:29 a.m. |
| NEDg | Description generation | batch_69b225ee67c48190879edf50981641ab |
completed | March 12, 2026, 2:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b22659f79c81908f33769dff3cc57d |
completed | March 12, 2026, 2:35 a.m. |
Created at: March 8, 2026, 3:05 p.m.