Triple
T10372864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Oladipo |
E244426
|
entity |
| Predicate | hasSibling |
P363
|
FINISHED |
| Object | Kristine Oladipo |
E859756
|
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: Kristine Oladipo | Statement: [Victor Oladipo, hasSibling, Kristine Oladipo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kristine Oladipo Context triple: [Victor Oladipo, hasSibling, Kristine Oladipo]
-
A.
Kendra Oladipo
chosen
Kendra Oladipo is known as the sister of NBA player Victor Oladipo.
-
B.
Victoria Oladipo
Victoria Oladipo is known as the sister of NBA player Victor Oladipo.
-
C.
Tamika Nurse
Tamika Nurse is a former Canadian collegiate basketball player known for her time as a standout guard at the University of Oregon and Bowling Green State University.
-
D.
Kelsey Plum
Kelsey Plum is an American professional basketball player and prolific scoring guard, best known for her record-setting college career at Washington and success in the WNBA.
-
E.
Jessica Whiteside
Jessica Whiteside is a geologist and paleoclimatologist known for her research on ancient climate change and mass extinctions.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e97f8a148190bb04996132cd464a |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e6f30c88190992242b6e0c43581 |
completed | April 10, 2026, 4:37 a.m. |
Created at: April 6, 2026, 12:02 p.m.