Triple
T23161959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Ten Coach of the Year |
E578609
|
entity |
| Predicate | hasWinner |
P6361
|
FINISHED |
| Object |
Ed DeChellis
Ed DeChellis is an American college basketball coach best known for his tenure leading the Penn State Nittany Lions and later the Navy Midshipmen.
|
E1577942
|
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: Ed DeChellis | Statement: [Big Ten Coach of the Year, hasWinner, Ed DeChellis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ed DeChellis Context triple: [Big Ten Coach of the Year, hasWinner, Ed DeChellis]
-
A.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
-
B.
Michael Waddell
Michael Waddell is a sports executive best known for serving as president of the Orlando Apollos in the Alliance of American Football.
-
C.
Dave Quackenbush
Dave Quackenbush is an American punk rock vocalist best known as the longtime lead singer of the Southern California band The Vandals.
-
D.
Gordon Daugherty
Gordon Daugherty is a technology entrepreneur, investor, and startup advisor known for his work supporting early-stage companies and the Texas startup ecosystem.
-
E.
Phil Kellogg
Phil Kellogg is a music producer known for his work with the band American Heart.
- 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: Ed DeChellis Triple: [Big Ten Coach of the Year, hasWinner, Ed DeChellis]
Generated description
Ed DeChellis is an American college basketball coach best known for his tenure leading the Penn State Nittany Lions and later the Navy Midshipmen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ed DeChellis Target entity description: Ed DeChellis is an American college basketball coach best known for his tenure leading the Penn State Nittany Lions and later the Navy Midshipmen.
-
A.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
-
B.
Michael Waddell
Michael Waddell is a sports executive best known for serving as president of the Orlando Apollos in the Alliance of American Football.
-
C.
Dave Quackenbush
Dave Quackenbush is an American punk rock vocalist best known as the longtime lead singer of the Southern California band The Vandals.
-
D.
Gordon Daugherty
Gordon Daugherty is a technology entrepreneur, investor, and startup advisor known for his work supporting early-stage companies and the Texas startup ecosystem.
-
E.
Phil Kellogg
Phil Kellogg is a music producer known for his work with the band American Heart.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f019cd881908e3c68d99454da2a |
completed | April 29, 2026, 4:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3f428730819093c8c29d2f5b2c2a |
completed | May 19, 2026, 10:45 a.m. |
| NEDg | Description generation | batch_6a0c4075bc508190ae0dc8b61c24faa0 |
completed | May 19, 2026, 10:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c411702a48190ba2964ba221394d1 |
completed | May 19, 2026, 10:53 a.m. |
Created at: April 17, 2026, 4:02 p.m.