Triple
T10945185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Swanson |
E258576
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kevin |
E474898
|
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: Kevin | Statement: [Kevin Swanson, givenName, Kevin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kevin Context triple: [Kevin Swanson, givenName, Kevin]
-
A.
Kevin
chosen
Kevin is a common masculine given name of Irish origin, meaning "handsome" or "kind."
-
B.
Kevin
Kevin is the given first name of American actor and former professional athlete Chuck Connors.
-
C.
Kevin
Kevin is the given name of Kevin Garnett, a Hall of Fame American professional basketball player known for his intensity, versatility, and NBA championship with the Boston Celtics.
-
D.
Kevin
Kevin is the young boy protagonist of the 1981 fantasy adventure film "Time Bandits," who joins a group of time-traveling dwarfs on a series of historical escapades.
-
E.
Kevin
Kevin is a character in the play "Clybourne Park," serving as one of the contemporary residents whose interactions highlight ongoing racial and social tensions in the gentrifying neighborhood.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770e9a89081908979efd1d9e6af66 |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23c2dea008190af68336a096b7f7c |
completed | April 17, 2026, 1:57 p.m. |
Created at: April 8, 2026, 9:23 p.m.