Triple
T9735652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murderball |
E236049
|
entity |
| Predicate | featuresAthlete |
P17934
|
FINISHED |
| Object |
Mark Zupan
Mark Zupan is an American wheelchair rugby player and Paralympian best known for his prominent role in the documentary film "Murderball."
|
E818650
|
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: Mark Zupan | Statement: [Murderball, featuresAthlete, Mark Zupan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Zupan Context triple: [Murderball, featuresAthlete, Mark Zupan]
-
A.
Michael Kuzak
Michael Kuzak is a central attorney character on the television legal drama "L.A. Law," known for his idealism and high-profile courtroom battles.
-
B.
Mark Czyzewski
Mark Czyzewski is an editor known for his work on the film "Greyhound."
-
C.
Jeff Jagodzinski
Jeff Jagodzinski is an American football coach best known for his tenure as head coach at Boston College and his extensive experience as an offensive coach in both college football and the NFL.
-
D.
Brian Budzinski
Brian Budzinski is a sports executive best known for his role as an owner of the National Women's Soccer League club FC Kansas City.
-
E.
Jack Zivic
Jack Zivic was an American professional boxer active in the early 20th century, known as one of the fighting Zivic brothers from Pittsburgh.
- 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: Mark Zupan Triple: [Murderball, featuresAthlete, Mark Zupan]
Generated description
Mark Zupan is an American wheelchair rugby player and Paralympian best known for his prominent role in the documentary film "Murderball."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Zupan Target entity description: Mark Zupan is an American wheelchair rugby player and Paralympian best known for his prominent role in the documentary film "Murderball."
-
A.
Michael Kuzak
Michael Kuzak is a central attorney character on the television legal drama "L.A. Law," known for his idealism and high-profile courtroom battles.
-
B.
Mark Czyzewski
Mark Czyzewski is an editor known for his work on the film "Greyhound."
-
C.
Jeff Jagodzinski
Jeff Jagodzinski is an American football coach best known for his tenure as head coach at Boston College and his extensive experience as an offensive coach in both college football and the NFL.
-
D.
Brian Budzinski
Brian Budzinski is a sports executive best known for his role as an owner of the National Women's Soccer League club FC Kansas City.
-
E.
Jack Zivic
Jack Zivic was an American professional boxer active in the early 20th century, known as one of the fighting Zivic brothers from Pittsburgh.
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9eee70d48190af5a833d7b33aaa5 |
completed | April 1, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1afce9834819090949690b4ca8622 |
completed | April 5, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_69d1b098c3348190a298cfe4921c8921 |
completed | April 5, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1b124659481909e7a2ecaf01d8a50 |
completed | April 5, 2026, 12:47 a.m. |
Created at: March 30, 2026, 8:22 p.m.