Triple
T806296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnold Schwarzenegger |
E17440
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object |
Mr. Olympia
Mr. Olympia is the premier annual professional bodybuilding competition that crowns the world’s top male bodybuilder.
|
E95774
|
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: Mr. Olympia | Statement: [Arnold Schwarzenegger, title, Mr. Olympia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Olympia Context triple: [Arnold Schwarzenegger, title, Mr. Olympia]
-
A.
Mr. Universe
Mr. Universe is a stand-up comedy special by Jim Gaffigan known for his observational humor and family-friendly, self-deprecating style.
-
B.
MEN Arena
MEN Arena was the former name of Manchester Arena, a major indoor entertainment and sports venue in Manchester, England.
-
C.
Hulk Hogan
Hulk Hogan is an iconic American professional wrestler and pop culture figure who became one of the most recognizable stars of the 1980s and 1990s sports entertainment boom.
-
D.
Undisputed
Undisputed is a sports debate television show, best known for its outspoken commentary and heated discussions on major sports topics.
-
E.
Tyson
Tyson is the surname of Neil deGrasse Tyson, the prominent American astrophysicist, author, and science communicator.
- 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: Mr. Olympia Triple: [Arnold Schwarzenegger, title, Mr. Olympia]
Generated description
Mr. Olympia is the premier annual professional bodybuilding competition that crowns the world’s top male bodybuilder.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mr. Olympia Target entity description: Mr. Olympia is the premier annual professional bodybuilding competition that crowns the world’s top male bodybuilder.
-
A.
Mr. Universe
Mr. Universe is a stand-up comedy special by Jim Gaffigan known for his observational humor and family-friendly, self-deprecating style.
-
B.
MEN Arena
MEN Arena was the former name of Manchester Arena, a major indoor entertainment and sports venue in Manchester, England.
-
C.
Hulk Hogan
Hulk Hogan is an iconic American professional wrestler and pop culture figure who became one of the most recognizable stars of the 1980s and 1990s sports entertainment boom.
-
D.
Undisputed
Undisputed is a sports debate television show, best known for its outspoken commentary and heated discussions on major sports topics.
-
E.
Tyson
Tyson is the surname of Neil deGrasse Tyson, the prominent American astrophysicist, author, and science communicator.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4aac1142881908f6f78bfdb887930 |
completed | March 1, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a68927ba948190999fd1459dd62cca |
completed | March 3, 2026, 7:09 a.m. |
| NEDg | Description generation | batch_69a6dcb16cf4819084f28de3328a0073 |
completed | March 3, 2026, 1:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a75e9333e48190914827eb0267abd0 |
completed | March 3, 2026, 10:20 p.m. |
Created at: March 1, 2026, 7:38 p.m.