Triple
T1231996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chauncey Billups |
E26461
|
entity |
| Predicate | wonMedal |
P15190
|
FINISHED |
| Object | gold medal at FIBA Americas Championship 2007 |
—
|
LITERAL 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: gold medal at FIBA Americas Championship 2007 | Statement: [Chauncey Billups, wonMedal, gold medal at FIBA Americas Championship 2007]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonMedal Context triple: [Chauncey Billups, wonMedal, gold medal at FIBA Americas Championship 2007]
-
A.
goldMedalist
chosen
Indicates that the subject is the winner of a first-place gold medal in a competition or event.
-
B.
OlympicMedal
Indicates that an entity has been awarded an Olympic medal in a specific event or discipline.
-
C.
medalAwardedToWinner
Indicates that a medal is given to the entity that has won a competition or contest.
-
D.
silverMedalist
Indicates that an entity finished in second place in a competition or event, earning the silver medal.
-
E.
bronzeMedalist
Indicates that an entity finished third in a competition or event, earning the bronze medal.
- F. None of above.
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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5a25348190a0665b6324c4d8f5 |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb65d61c8190bf0424ea0019a98b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.