Triple
T23407183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germantown Academy |
E559964
|
entity |
| Predicate | hasAlumnus |
P51
|
FINISHED |
| Object | Kyle Lowry |
—
|
NE NERFINISHED |
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: Kyle Lowry | Statement: [Germantown Academy, hasAlumnus, Kyle Lowry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyle Lowry Context triple: [Germantown Academy, hasAlumnus, Kyle Lowry]
-
A.
Kyle Lowry
chosen
Kyle Lowry is an American professional basketball point guard best known for his leadership and playmaking during the Toronto Raptors’ rise to NBA championship contention.
-
B.
Kelly Olynyk
Kelly Olynyk is a Canadian professional basketball player and NBA veteran known for his versatile scoring and playmaking as a stretch big man.
-
C.
Dwayne Mitchell
Dwayne Mitchell is a music producer known for his work on Brian McKnight’s self-titled debut album.
-
D.
Richard Van Vleet
Richard Van Vleet is an American actor best known for his long-running role as Dr. Chuck Tyler on the soap opera "All My Children."
-
E.
Tyler Ennis
Tyler Ennis is a Canadian professional ice hockey center who has played in the NHL for multiple teams, known for his speed, offensive skill, and playmaking ability.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a50e607c8190ba0a22e89862a2d9 |
completed | April 29, 2026, 6:28 a.m. |
Created at: April 17, 2026, 5:38 p.m.