Triple
T18262270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thea Kronborg |
E437386
|
entity |
| Predicate | hasMentor |
P25349
|
FINISHED |
| Object | Andor Harsanyi |
—
|
NE NERFINISHED |
How this triple was built (3 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: Andor Harsanyi | Statement: [Thea Kronborg, hasMentor, Andor Harsanyi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andor Harsanyi Context triple: [Thea Kronborg, hasMentor, Andor Harsanyi]
-
A.
John Harsanyi
John Harsanyi was a Hungarian-American economist and Nobel laureate renowned for his foundational contributions to game theory and welfare economics, particularly his work on modeling rational behavior and social choice under uncertainty.
-
B.
Oskar Morgenstern
Oskar Morgenstern was an Austrian-American economist best known as the co-founder of game theory through his seminal work "Theory of Games and Economic Behavior" with John von Neumann.
-
C.
László Kalmár
László Kalmár was a Hungarian mathematician known as a pioneer of theoretical computer science and mathematical logic in Hungary.
-
D.
Lajos Takács
Lajos Takács was a Hungarian-American mathematician renowned for his pioneering contributions to probability theory and queueing theory.
-
E.
Mihály Neumann
Mihály Neumann was a member of the prominent Hungarian-Jewish von Neumann family, known for producing influential figures in mathematics and science.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andor Harsanyi Target entity description: Andor Harsanyi is a fictional music teacher and mentor in Willa Cather’s novel "The Song of the Lark," who guides the artistic development of the protagonist, Thea Kronborg.
-
A.
John Harsanyi
John Harsanyi was a Hungarian-American economist and Nobel laureate renowned for his foundational contributions to game theory and welfare economics, particularly his work on modeling rational behavior and social choice under uncertainty.
-
B.
Oskar Morgenstern
Oskar Morgenstern was an Austrian-American economist best known as the co-founder of game theory through his seminal work "Theory of Games and Economic Behavior" with John von Neumann.
-
C.
László Kalmár
László Kalmár was a Hungarian mathematician known as a pioneer of theoretical computer science and mathematical logic in Hungary.
-
D.
Lajos Takács
Lajos Takács was a Hungarian-American mathematician renowned for his pioneering contributions to probability theory and queueing theory.
-
E.
Mihály Neumann
Mihály Neumann was a member of the prominent Hungarian-Jewish von Neumann family, known for producing influential figures in mathematics and science.
- F. None of above. chosen
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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff76a1208190abbe6ab8720ed154 |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 10, 2026, 10:34 a.m.