Triple
T9429249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilco |
E227330
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Glenn Kotche
Glenn Kotche is an American drummer and composer best known as the innovative percussionist for the rock band Wilco.
|
E799581
|
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: Glenn Kotche | Statement: [Wilco, hasMember, Glenn Kotche]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glenn Kotche Context triple: [Wilco, hasMember, Glenn Kotche]
-
A.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
B.
Ken Koblun
Ken Koblun is a Canadian bassist best known for his early involvement with the influential 1960s rock band Buffalo Springfield.
-
C.
Joel McNeely
Joel McNeely is an American composer and conductor best known for his work on film and television scores, including numerous projects for Disney and other major studios.
-
D.
Jim McKenny
Jim McKenny is a former Canadian professional ice hockey defenceman best known for his years with the Toronto Maple Leafs and later work as a Toronto sports broadcaster.
-
E.
Thom Beers
Thom Beers is an American television producer and narrator best known for creating and producing gritty, reality-based series such as "Deadliest Catch" and other shows focused on dangerous occupations and extreme situations.
- 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: Glenn Kotche Triple: [Wilco, hasMember, Glenn Kotche]
Generated description
Glenn Kotche is an American drummer and composer best known as the innovative percussionist for the rock band Wilco.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Glenn Kotche Target entity description: Glenn Kotche is an American drummer and composer best known as the innovative percussionist for the rock band Wilco.
-
A.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
B.
Ken Koblun
Ken Koblun is a Canadian bassist best known for his early involvement with the influential 1960s rock band Buffalo Springfield.
-
C.
Joel McNeely
Joel McNeely is an American composer and conductor best known for his work on film and television scores, including numerous projects for Disney and other major studios.
-
D.
Jim McKenny
Jim McKenny is a former Canadian professional ice hockey defenceman best known for his years with the Toronto Maple Leafs and later work as a Toronto sports broadcaster.
-
E.
Thom Beers
Thom Beers is an American television producer and narrator best known for creating and producing gritty, reality-based series such as "Deadliest Catch" and other shows focused on dangerous occupations and extreme situations.
- 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_69ca8436ba308190903e470776d2d893 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7c94719c81909d7743a57c45e07f |
completed | April 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d11038f7b88190bd6b895f5544c63e |
completed | April 4, 2026, 1:20 p.m. |
| NEDg | Description generation | batch_69d111a770c881909a2902d36cd7913c |
completed | April 4, 2026, 1:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d112634fb48190b4c7e9d997d27928 |
completed | April 4, 2026, 1:30 p.m. |
Created at: March 30, 2026, 7:49 p.m.