Triple
T19413221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NXTHVN |
E485641
|
entity |
| Predicate | coFoundedBy |
P3263
|
FINISHED |
| Object | Jonathan Brand |
—
|
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: Jonathan Brand | Statement: [NXTHVN, coFoundedBy, Jonathan Brand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Brand Context triple: [NXTHVN, coFoundedBy, Jonathan Brand]
-
A.
Jonathan Brand
chosen
Jonathan Brand is an American academic administrator and lawyer who serves as the president of Cornell College in Mount Vernon, Iowa.
-
B.
Michael Brandman
Michael Brandman is an American film and television producer and writer known for adapting and producing literary and theatrical works.
-
C.
Joe Brandt
Joe Brandt was an American film industry executive and producer best known as one of the co-founders of Columbia Pictures.
-
D.
Mark Brandenburg
Mark Brandenburg is a historic region in northeastern Germany that formed the core of the medieval Margraviate of Brandenburg and later became central to the rise of Prussia.
-
E.
Michael Bruxner
Michael Bruxner was an Australian politician and long-serving leader of the Country Party in New South Wales, noted for his influence on rural policy and infrastructure development.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af77eb481909fcfb6cdde1e8580 |
completed | April 20, 2026, 1:32 p.m. |
Created at: April 10, 2026, 1:37 p.m.