Triple
T15430401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dwayne Bacon |
E369621
|
entity |
| Predicate | participantIn |
P149
|
FINISHED |
| Object | LNB Pro A |
E309573
|
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: LNB Pro A | Statement: [Dwayne Bacon, participantIn, LNB Pro A]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LNB Pro A Context triple: [Dwayne Bacon, participantIn, LNB Pro A]
-
A.
LNB Pro A
chosen
LNB Pro A is the top-tier professional men's basketball league in France.
-
B.
LNB Pro B
LNB Pro B is the second-tier professional men's basketball league in France, sitting just below the top-level LNB Pro A.
-
C.
Lega Basket Serie A
Lega Basket Serie A is Italy’s top professional basketball league, featuring the country’s premier clubs and serving as a key stage for European and international talent.
-
D.
B3 League
The B3 League is a professional Japanese basketball league that functions as the third tier beneath the top-level B.League divisions.
-
E.
B2 League
The B2 League is the second-tier professional basketball league in Japan, sitting just below the top-level B.League.
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ed8ea888190bff8dc14859cca31 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a827d9081909fabc48bc685ba5b |
completed | May 9, 2026, 11:29 a.m. |
Created at: April 10, 2026, 3:21 a.m.