Triple
T6523744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 MLS Cup |
E151249
|
entity |
| Predicate | awayManager |
P5837
|
FINISHED |
| Object | Brian Schmetzer |
E243613
|
NE FINISHED |
How this triple was built (2 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: Brian Schmetzer | Statement: [2017 MLS Cup, awayManager, Brian Schmetzer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Schmetzer Context triple: [2017 MLS Cup, awayManager, Brian Schmetzer]
-
A.
Brian Schmetzer
chosen
Brian Schmetzer is an American soccer coach best known for leading Seattle Sounders FC to multiple MLS Cup titles and establishing the club as a perennial league contender.
-
B.
Ken Schretzmann
Ken Schretzmann is a film editor known for his work on major animated features, including Guillermo del Toro's stop-motion adaptation of Pinocchio.
-
C.
Kevin Riepl
Kevin Riepl is an American composer best known for his atmospheric scores for films and video games, including work on titles like Gears of War and various horror and sci-fi projects.
-
D.
Eric Wetzels
Eric Wetzels is a Dutch politician who serves as the chairperson of the People's Party for Freedom and Democracy (VVD).
-
E.
Neil Kopp
Neil Kopp is an American film producer known for his work on acclaimed independent films, including the thriller "Green Room."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ad970afc81909d3231203eacf413 |
completed | March 27, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70064bfa48190bbb5b4f92dde8dde |
completed | March 27, 2026, 10:10 p.m. |
Created at: March 27, 2026, 1:45 p.m.