Triple
T20766279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manfred Eigen |
E511106
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Eigen
Eigen is a German surname most notably associated with Nobel Prize–winning biophysical chemist Manfred Eigen.
|
E1449702
|
NE FINISHED |
How this triple was built (4 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: Eigen | Statement: [Manfred Eigen, familyName, Eigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eigen Context triple: [Manfred Eigen, familyName, Eigen]
-
A.
Sophus
Sophus was the given name of the Norwegian mathematician Sophus Lie, a pioneer in the theory of continuous transformation groups now known as Lie groups.
-
B.
LinearAlgebra
LinearAlgebra is Julia’s standard library module providing core functionality for vectors, matrices, and advanced linear algebra operations.
-
C.
Jacobi eigenvalue algorithm
The Jacobi eigenvalue algorithm is an iterative numerical method for computing all eigenvalues and eigenvectors of a real symmetric matrix by applying a sequence of orthogonal similarity transformations.
-
D.
EISPACK
EISPACK is a numerical software library written in Fortran for computing eigenvalues and eigenvectors of matrices, widely used before being superseded by LAPACK.
-
E.
arpack
arpack is a numerical software library for efficiently computing a few eigenvalues and eigenvectors of large sparse matrices, commonly used in scientific computing and machine learning.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Eigen Triple: [Manfred Eigen, familyName, Eigen]
Generated description
Eigen is a German surname most notably associated with Nobel Prize–winning biophysical chemist Manfred Eigen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eigen Target entity description: Eigen is a German surname most notably associated with Nobel Prize–winning biophysical chemist Manfred Eigen.
-
A.
Sophus
Sophus was the given name of the Norwegian mathematician Sophus Lie, a pioneer in the theory of continuous transformation groups now known as Lie groups.
-
B.
LinearAlgebra
LinearAlgebra is Julia’s standard library module providing core functionality for vectors, matrices, and advanced linear algebra operations.
-
C.
Jacobi eigenvalue algorithm
The Jacobi eigenvalue algorithm is an iterative numerical method for computing all eigenvalues and eigenvectors of a real symmetric matrix by applying a sequence of orthogonal similarity transformations.
-
D.
EISPACK
EISPACK is a numerical software library written in Fortran for computing eigenvalues and eigenvectors of matrices, widely used before being superseded by LAPACK.
-
E.
arpack
arpack is a numerical software library for efficiently computing a few eigenvalues and eigenvectors of large sparse matrices, commonly used in scientific computing and machine learning.
- F. None of above. chosen
Provenance (5 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24ceab8819094e331c57abe6879 |
completed | April 21, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08ef8b07648190bac0f417a4aa06bc |
completed | May 16, 2026, 10:28 p.m. |
| NEDg | Description generation | batch_6a08f23554208190aa1dc7294ab62e6c |
completed | May 16, 2026, 10:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08f2a50c1c8190b167334fce4121cc |
completed | May 16, 2026, 10:41 p.m. |
Created at: April 16, 2026, 12:36 p.m.