Triple
T13103629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tampa Bay Mutiny |
E310783
|
entity |
| Predicate | notablePlayer |
P304
|
FINISHED |
| Object | Steve Ralston |
E580850
|
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: Steve Ralston | Statement: [Tampa Bay Mutiny, notablePlayer, Steve Ralston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Ralston Context triple: [Tampa Bay Mutiny, notablePlayer, Steve Ralston]
-
A.
Steve Ralston
chosen
Steve Ralston is a former American soccer midfielder best known as a longtime MLS standout and U.S. national team player, particularly with the New England Revolution.
-
B.
Matthew Rolston
Matthew Rolston is an American photographer and director renowned for his stylized celebrity portraiture and visually distinctive music videos.
-
C.
Brian Routh
Brian Routh was a British performance artist and musician best known as one half of the avant-garde comedy and performance duo The Kipper Kids.
-
D.
Jonathan Ralston
Jonathan Ralston, known as Reb Ralston, is an individual primarily recognized by this nickname, though little widely known public information is available about him.
-
E.
Ken Ralston
Ken Ralston is an acclaimed visual effects supervisor known for his groundbreaking work on major films such as the Star Wars and Back to the Future series.
- 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_69f7ce5d00888190af03d9ef287f421f |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 9:04 p.m.