Triple
T19214413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Schott |
E480442
|
entity |
| Predicate | coOwnerWith |
P3498
|
FINISHED |
| Object |
Ken Hofmann
Ken Hofmann was an American real estate developer and sports team owner best known for co-owning Major League Baseball’s Oakland Athletics.
|
E1410650
|
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: Ken Hofmann | Statement: [Stephen Schott, coOwnerWith, Ken Hofmann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Hofmann Context triple: [Stephen Schott, coOwnerWith, Ken Hofmann]
-
A.
Ken Wiederhorn
Ken Wiederhorn is an American film director best known for his work in 1980s genre cinema, including cult horror and comedy films.
-
B.
Eric Schoffstall
Eric Schoffstall is a software developer best known for creating Gulp, a popular JavaScript-based task runner used in web development build workflows.
-
C.
Ken Lauber
Ken Lauber is an American composer and musician known for his film and television scores, blending elements of jazz, classical, and popular music.
-
D.
Craig Huffstodt
Craig Huffstodt is the troubled psychiatrist protagonist of the television drama series "Huff," portrayed by actor Hank Azaria.
-
E.
Jon Hoeber
Jon Hoeber is an American screenwriter best known for co-writing action and thriller films such as "Red" and its sequel, as well as various big-budget genre movies.
- 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: Ken Hofmann Triple: [Stephen Schott, coOwnerWith, Ken Hofmann]
Generated description
Ken Hofmann was an American real estate developer and sports team owner best known for co-owning Major League Baseball’s Oakland Athletics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ken Hofmann Target entity description: Ken Hofmann was an American real estate developer and sports team owner best known for co-owning Major League Baseball’s Oakland Athletics.
-
A.
Ken Wiederhorn
Ken Wiederhorn is an American film director best known for his work in 1980s genre cinema, including cult horror and comedy films.
-
B.
Eric Schoffstall
Eric Schoffstall is a software developer best known for creating Gulp, a popular JavaScript-based task runner used in web development build workflows.
-
C.
Ken Lauber
Ken Lauber is an American composer and musician known for his film and television scores, blending elements of jazz, classical, and popular music.
-
D.
Craig Huffstodt
Craig Huffstodt is the troubled psychiatrist protagonist of the television drama series "Huff," portrayed by actor Hank Azaria.
-
E.
Jon Hoeber
Jon Hoeber is an American screenwriter best known for co-writing action and thriller films such as "Red" and its sequel, as well as various big-budget genre movies.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa397c188190b85bcfd9afd8dce6 |
completed | April 20, 2026, 10:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a081f1f42bc8190b89152f422a1b0e0 |
completed | May 16, 2026, 7:39 a.m. |
| NEDg | Description generation | batch_6a08209695e881908cb1afe6e17cd97d |
completed | May 16, 2026, 7:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08245621948190a7ae6f5e25b08a10 |
completed | May 16, 2026, 8:01 a.m. |
Created at: April 10, 2026, 1:22 p.m.