Triple
T1332032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2008 MLS Cup |
E28663
|
entity |
| Predicate | goalScorer |
P2695
|
FINISHED |
| Object |
John Wolyniec
John Wolyniec is a former American professional soccer forward best known for his time with the New York/New Jersey MetroStars and New York Red Bulls in Major League Soccer.
|
E170130
|
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: John Wolyniec | Statement: [2008 MLS Cup, goalScorer, John Wolyniec]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Wolyniec Context triple: [2008 MLS Cup, goalScorer, John Wolyniec]
-
A.
Stefan Rowecki
Stefan Rowecki was a Polish general and key leader of the World War II resistance movement, serving as commander of the underground Home Army against Nazi occupation.
-
B.
Andrew Goczkowski
Andrew Goczkowski is an American local government leader serving as the mayor of Des Plaines, Illinois.
-
C.
Stefan Osiecki
Stefan Osiecki was a Polish mountaineer known for pioneering ascents in remote regions, including major peaks in Patagonia.
-
D.
Mike Konopacki
Mike Konopacki is an American political cartoonist known for his labor- and social-justice-focused comics and graphic works.
-
E.
Daniel Dubiecki
Daniel Dubiecki is an American film producer known for his work on acclaimed movies such as "Up in the Air" and other high-profile Hollywood projects.
- 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: John Wolyniec Triple: [2008 MLS Cup, goalScorer, John Wolyniec]
Generated description
John Wolyniec is a former American professional soccer forward best known for his time with the New York/New Jersey MetroStars and New York Red Bulls in Major League Soccer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Wolyniec Target entity description: John Wolyniec is a former American professional soccer forward best known for his time with the New York/New Jersey MetroStars and New York Red Bulls in Major League Soccer.
-
A.
Stefan Rowecki
Stefan Rowecki was a Polish general and key leader of the World War II resistance movement, serving as commander of the underground Home Army against Nazi occupation.
-
B.
Andrew Goczkowski
Andrew Goczkowski is an American local government leader serving as the mayor of Des Plaines, Illinois.
-
C.
Stefan Osiecki
Stefan Osiecki was a Polish mountaineer known for pioneering ascents in remote regions, including major peaks in Patagonia.
-
D.
Mike Konopacki
Mike Konopacki is an American political cartoonist known for his labor- and social-justice-focused comics and graphic works.
-
E.
Daniel Dubiecki
Daniel Dubiecki is an American film producer known for his work on acclaimed movies such as "Up in the Air" and other high-profile Hollywood projects.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c5f86c819098e98b046968954a |
completed | March 1, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1c95b09881909e621ee55cdc7279 |
completed | March 8, 2026, 6:52 a.m. |
| NEDg | Description generation | batch_69ad1d816dac8190bf875e913c9164dc |
completed | March 8, 2026, 6:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad1e2b06548190be7755f9fc1c82ac |
completed | March 8, 2026, 6:58 a.m. |
Created at: March 1, 2026, 7:55 p.m.