Triple
T19751559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Sweet |
E474387
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Ossian Sweet |
—
|
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: Ossian Sweet | Statement: [Henry Sweet, sibling, Ossian Sweet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ossian Sweet Context triple: [Henry Sweet, sibling, Ossian Sweet]
-
A.
Ossian Sweet
chosen
Ossian Sweet was an African American physician whose 1925 trial for defending his Detroit home against a white mob became a landmark civil rights case.
-
B.
Ossian Kelly Ingram
Ossian Kelly Ingram was a U.S. Navy sailor and Medal of Honor recipient from World War I, commemorated for his bravery and sacrifice.
-
C.
OJ Haywood
OJ Haywood is the quiet, determined horse rancher protagonist of Jordan Peele’s sci-fi horror film "Nope."
-
D.
Gatemouth Brown
Gatemouth Brown was an American multi-instrumentalist and genre-blending musician best known for his innovative work in blues, country, jazz, and Cajun music.
-
E.
Solomon Song
"Solomon Song" is a musical number associated with the character Jenny Diver in the classic German musical drama "The Threepenny Opera" by Bertolt Brecht and Kurt Weill.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65299a7048190a9b22307ac06bd03 |
completed | April 20, 2026, 4:21 p.m. |
Created at: April 10, 2026, 1:48 p.m.