Triple
T13103630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tampa Bay Mutiny |
E310783
|
entity |
| Predicate | notableCoach |
P550
|
FINISHED |
| Object | Thomas Rongen |
E156867
|
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: Thomas Rongen | Statement: [Tampa Bay Mutiny, notableCoach, Thomas Rongen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Rongen Context triple: [Tampa Bay Mutiny, notableCoach, Thomas Rongen]
-
A.
Thomas Rongen
chosen
Thomas Rongen is a Dutch-American soccer coach and former player known for his extensive coaching career in Major League Soccer and with various U.S. national youth teams.
-
B.
John Verhoogen
John Verhoogen was a prominent 20th-century geophysicist known for his influential work on the thermal and dynamic evolution of the Earth’s interior.
-
C.
John Van Tongeren
John Van Tongeren is a film and television composer known for scoring movies such as "Miss Congeniality 2: Armed and Fabulous."
-
D.
Pieter R. de Jong
Pieter R. de Jong is a Dutch professional who studied at Utrecht University and is recognized as a notable alumnus for his contributions in his field.
-
E.
Jan T. Kleyna
Jan T. Kleyna is an astronomer known for discovering outer irregular moons of Jupiter, including Taygete.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98153255c8190b6ab64ac0c4716f8 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716bcbd188190ac74560a5f9e3654 |
completed | May 3, 2026, 9:34 a.m. |
Created at: April 9, 2026, 9:04 p.m.