Triple
T12688594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Dakota Coyotes |
E303142
|
entity |
| Predicate | athleticDirector |
P745
|
FINISHED |
| Object |
David Herbster
David Herbster is a collegiate sports administrator best known for serving as the athletic director at the University of South Dakota.
|
E998996
|
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: David Herbster | Statement: [South Dakota Coyotes, athleticDirector, David Herbster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Herbster Context triple: [South Dakota Coyotes, athleticDirector, David Herbster]
-
A.
Daniel Roher
Daniel Roher is a Canadian documentary filmmaker best known for directing the Oscar-winning political documentary "Navalny."
-
B.
Joseph Wintergerst
Joseph Wintergerst was a 19th-century German painter and art teacher associated with the Nazarene movement and early Romantic religious art.
-
C.
Jeremy Furstenfeld
Jeremy Furstenfeld is the drummer of the American alternative rock band Blue October.
-
D.
Michael Hecht
Michael Hecht is the birth name of Michael Howard, a British Conservative politician who served as Leader of the Opposition and Home Secretary.
-
E.
Michael Hecht
Michael Hecht is a scientist best known for leading NASA’s MOXIE experiment on the Perseverance rover, which demonstrates in-situ oxygen production on Mars.
- 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: David Herbster Triple: [South Dakota Coyotes, athleticDirector, David Herbster]
Generated description
David Herbster is a collegiate sports administrator best known for serving as the athletic director at the University of South Dakota.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Herbster Target entity description: David Herbster is a collegiate sports administrator best known for serving as the athletic director at the University of South Dakota.
-
A.
Daniel Roher
Daniel Roher is a Canadian documentary filmmaker best known for directing the Oscar-winning political documentary "Navalny."
-
B.
Joseph Wintergerst
Joseph Wintergerst was a 19th-century German painter and art teacher associated with the Nazarene movement and early Romantic religious art.
-
C.
Jeremy Furstenfeld
Jeremy Furstenfeld is the drummer of the American alternative rock band Blue October.
-
D.
Michael Hecht
Michael Hecht is the birth name of Michael Howard, a British Conservative politician who served as Leader of the Opposition and Home Secretary.
-
E.
Michael Hecht
Michael Hecht is a scientist best known for leading NASA’s MOXIE experiment on the Perseverance rover, which demonstrates in-situ oxygen production on Mars.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961d8cb048190864a85dd75648820 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671aacfa8819088fd113474638238 |
completed | May 2, 2026, 9:50 p.m. |
| NEDg | Description generation | batch_69f6751f79148190a1735abf489fd106 |
completed | May 2, 2026, 10:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f675c42fec8190b60751c0db88f3b6 |
completed | May 2, 2026, 10:08 p.m. |
Created at: April 9, 2026, 5:21 p.m.