Triple
T31080630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Julius Bernstein |
E792084
|
entity |
| Predicate | hasMathematicsGenealogyProjectId |
P201437
|
FINISHED |
| Object | 41056 |
—
|
LITERAL 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: 41056 | Statement: [Daniel Julius Bernstein, hasMathematicsGenealogyProjectId, 41056]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMathematicsGenealogyProjectId Context triple: [Daniel Julius Bernstein, hasMathematicsGenealogyProjectId, 41056]
-
A.
hasMathematicalDiscipline
Indicates that one entity is associated with or characterized by a particular branch or field of mathematics.
-
B.
hasMathematicalInterest
Indicates that one entity has an interest in, curiosity about, or engagement with mathematics in relation to another entity or mathematical subject.
-
C.
hasMathematicalTopic
Indicates that one entity is associated with, involves, or is about a particular mathematical topic represented by the other entity.
-
D.
hasMathematicalProperty
Indicates that one entity possesses or exhibits a specific mathematical property or characteristic.
-
E.
relatedMathematician
Indicates that there is a notable mathematical connection or association between the two entities, such as influence, collaboration, or work on related topics.
- F. None of above. chosen
Provenance (4 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_69f224ccdbbc81909b0cdb4cc2d70c7a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fff59a00a881909b35b799654b3c45 |
completed | May 10, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69fff4d0a2e081909c972189b33d0128 |
completed | May 10, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69fff59875cc8190864864e951951679 |
completed | May 10, 2026, 3:03 a.m. |
Created at: April 29, 2026, 9:02 p.m.