Triple
T767518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Frisch |
E16207
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Stiller
Stiller is a 1954 novel by Swiss author Max Frisch that explores themes of identity, self-deception, and the impossibility of truly knowing oneself.
|
E91531
|
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: Stiller | Statement: [Max Frisch, notableWork, Stiller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stiller Context triple: [Max Frisch, notableWork, Stiller]
-
A.
John Ferrell
John Ferrell was a photographer for the U.S. Farm Security Administration, contributing documentary images of American life during the Great Depression and World War II era.
-
B.
Farley
Farley is a surname most notably associated with Jim Farley, an American business executive and CEO of Ford Motor Company.
-
C.
Jeffrey Dean
Jeffrey Dean is a prominent American computer scientist and software engineer best known for his influential work on large-scale distributed systems and infrastructure at Google.
-
D.
Timothy Black
Timothy Black is a relatively obscure individual whose specific public notability is not clearly established from the given information.
-
E.
Mulally
Mulally is the surname of Alan Mulally, the American engineer and former CEO known for leading major turnarounds at Boeing and Ford Motor Company.
- 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: Stiller Triple: [Max Frisch, notableWork, Stiller]
Generated description
Stiller is a 1954 novel by Swiss author Max Frisch that explores themes of identity, self-deception, and the impossibility of truly knowing oneself.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stiller Target entity description: Stiller is a 1954 novel by Swiss author Max Frisch that explores themes of identity, self-deception, and the impossibility of truly knowing oneself.
-
A.
John Ferrell
John Ferrell was a photographer for the U.S. Farm Security Administration, contributing documentary images of American life during the Great Depression and World War II era.
-
B.
Farley
Farley is a surname most notably associated with Jim Farley, an American business executive and CEO of Ford Motor Company.
-
C.
Jeffrey Dean
Jeffrey Dean is a prominent American computer scientist and software engineer best known for his influential work on large-scale distributed systems and infrastructure at Google.
-
D.
Timothy Black
Timothy Black is a relatively obscure individual whose specific public notability is not clearly established from the given information.
-
E.
Mulally
Mulally is the surname of Alan Mulally, the American engineer and former CEO known for leading major turnarounds at Boeing and Ford Motor Company.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a6a0fee08190bf365d14c007e008 |
completed | March 1, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a666760a4c8190afd00dbfc263be28 |
completed | March 3, 2026, 4:41 a.m. |
| NEDg | Description generation | batch_69a66a6289a881909a2ada9c8a5ea091 |
completed | March 3, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a66ad0da0081909fc828eccabf5b80 |
completed | March 3, 2026, 5 a.m. |
Created at: March 1, 2026, 7:37 p.m.