Triple
T2301348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEP 622 |
E51738
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object |
Tobias Kohn
Tobias Kohn is a computer scientist and software developer known for his contributions to the Python language, including co-authoring PEP 622 on pattern matching.
|
E253902
|
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: Tobias Kohn | Statement: [PEP 622, author, Tobias Kohn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tobias Kohn Context triple: [PEP 622, author, Tobias Kohn]
-
A.
Tobias Fünke
Tobias Fünke is a socially awkward, aspiring actor and former analyst-therapist known for his oblivious behavior and unintentional double entendres in the television series "Arrested Development."
-
B.
Markus Morgenstern
Markus Morgenstern is a mathematician known for his contributions to combinatorics and graph theory.
-
C.
Christopher Scholz
Christopher Scholz is a prominent geophysicist renowned for his influential work on the mechanics of earthquakes and faulting.
-
D.
Michael Ohoven
Michael Ohoven is a German film producer and founder of Infinity Media, known for producing acclaimed independent films such as "Capote."
-
E.
Gerwin Klein
Gerwin Klein is a computer scientist known for his work in formal verification, particularly the seL4 microkernel verification project.
- 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: Tobias Kohn Triple: [PEP 622, author, Tobias Kohn]
Generated description
Tobias Kohn is a computer scientist and software developer known for his contributions to the Python language, including co-authoring PEP 622 on pattern matching.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tobias Kohn Target entity description: Tobias Kohn is a computer scientist and software developer known for his contributions to the Python language, including co-authoring PEP 622 on pattern matching.
-
A.
Tobias Fünke
Tobias Fünke is a socially awkward, aspiring actor and former analyst-therapist known for his oblivious behavior and unintentional double entendres in the television series "Arrested Development."
-
B.
Markus Morgenstern
Markus Morgenstern is a mathematician known for his contributions to combinatorics and graph theory.
-
C.
Christopher Scholz
Christopher Scholz is a prominent geophysicist renowned for his influential work on the mechanics of earthquakes and faulting.
-
D.
Michael Ohoven
Michael Ohoven is a German film producer and founder of Infinity Media, known for producing acclaimed independent films such as "Capote."
-
E.
Gerwin Klein
Gerwin Klein is a computer scientist known for his work in formal verification, particularly the seL4 microkernel verification project.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5ef51948190ae828d8ee02feb75 |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f31356c81909c563d88d472e05f |
completed | March 9, 2026, 8:05 a.m. |
| NEDg | Description generation | batch_69ae7fd78ee48190990fc7b5034b662b |
completed | March 9, 2026, 8:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae80dadf208190913211329a40b4ee |
completed | March 9, 2026, 8:12 a.m. |
Created at: March 4, 2026, 7:49 p.m.