Triple
T10552764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SeatGeek |
E248994
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Jack Groetzinger
Jack Groetzinger is an American entrepreneur best known as a co-founder of the mobile-focused ticket marketplace SeatGeek.
|
E881363
|
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: Jack Groetzinger | Statement: [SeatGeek, foundedBy, Jack Groetzinger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Groetzinger Context triple: [SeatGeek, foundedBy, Jack Groetzinger]
-
A.
Paul Groesse
Paul Groesse was an Academy Award–winning Hollywood art director known for his work on classic mid-20th-century films.
-
B.
Frank Teschemacher
Frank Teschemacher was an influential early Chicago jazz clarinetist and saxophonist known for his role in shaping the Chicago style of the 1920s and early 1930s.
-
C.
John Reister
John Reister was an early settler and landowner after whom the community of Reisterstown, Maryland, was named.
-
D.
Albert Benitz
Albert Benitz was a German cinematographer known for his work on numerous films during the early to mid-20th century, including projects associated with Leni Riefenstahl.
-
E.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
- 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: Jack Groetzinger Triple: [SeatGeek, foundedBy, Jack Groetzinger]
Generated description
Jack Groetzinger is an American entrepreneur best known as a co-founder of the mobile-focused ticket marketplace SeatGeek.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jack Groetzinger Target entity description: Jack Groetzinger is an American entrepreneur best known as a co-founder of the mobile-focused ticket marketplace SeatGeek.
-
A.
Paul Groesse
Paul Groesse was an Academy Award–winning Hollywood art director known for his work on classic mid-20th-century films.
-
B.
Frank Teschemacher
Frank Teschemacher was an influential early Chicago jazz clarinetist and saxophonist known for his role in shaping the Chicago style of the 1920s and early 1930s.
-
C.
John Reister
John Reister was an early settler and landowner after whom the community of Reisterstown, Maryland, was named.
-
D.
Albert Benitz
Albert Benitz was a German cinematographer known for his work on numerous films during the early to mid-20th century, including projects associated with Leni Riefenstahl.
-
E.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d526d5820c8190a1ad6d6551d093bb |
completed | April 7, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbacc05334819081e994d75b5e9318 |
completed | April 12, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69dbaeb211088190a9118c71918584e5 |
completed | April 12, 2026, 2:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dbaf7c999c819097a8cdf5bd82f648 |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 6, 2026, 12:34 p.m.