Triple
T21972858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Stroock |
E542634
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Daniel Stroock |
—
|
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: Daniel Stroock | Statement: [Daniel Stroock, name, Daniel Stroock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Stroock Context triple: [Daniel Stroock, name, Daniel Stroock]
-
A.
Daniel Stroock
chosen
Daniel Stroock is an American mathematician renowned for his contributions to probability theory and stochastic processes.
-
B.
Loring W. Tu
Loring W. Tu is a mathematician known for his work in differential geometry and topology, including coauthoring the influential textbook "Differential Forms in Algebraic Topology."
-
C.
Michael Lehmann
Michael Lehmann is an American film and television director best known for the dark comedy "Heathers" and various other Hollywood comedies.
-
D.
Peter Librowski
Peter Librowski is a musician best known as a member of the rock band The Lords.
-
E.
Ken Rudin
Ken Rudin is a technology executive and entrepreneur best known for his leadership role in founding the enterprise software company Siebel Systems.
- 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_69e0c48070988190909db97667b9a0ac |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124857dcc8190ab474cd8ab9c130a |
completed | April 28, 2026, 9:20 p.m. |
Created at: April 16, 2026, 8:02 p.m.