Triple
T3301645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Vermes |
E69347
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Peter Vermes |
E69347
|
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: Peter Vermes | Statement: [Peter Vermes, name, Peter Vermes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Vermes Context triple: [Peter Vermes, name, Peter Vermes]
-
A.
Peter Vermes
chosen
Peter Vermes is an American soccer coach and former defender best known for his long tenure leading Sporting Kansas City in Major League Soccer.
-
B.
Sigi Schmid
Sigi Schmid was a highly successful German-American soccer coach best known for leading MLS clubs like the LA Galaxy, Columbus Crew, and Seattle Sounders to multiple league titles and trophies.
-
C.
Tom Nissalke
Tom Nissalke was an American professional basketball coach best known for his work in the ABA and NBA during the 1970s and 1980s.
-
D.
Jason Kreis
Jason Kreis is an American soccer coach and former player best known for leading Real Salt Lake to an MLS Cup title and later managing several Major League Soccer clubs.
-
E.
Pascal Jost
Pascal Jost is a French local politician serving as the mayor of the commune of Veckring in northeastern France.
- 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0a7d224819080d9a638e08bb8a8 |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3df7f548190ada47f742df46545 |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:11 p.m.