Triple
T738123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Econometrica |
E14979
|
entity |
| Predicate | founder |
P104
|
FINISHED |
| Object | Ragnar Frisch |
E26916
|
NE 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: Ragnar Frisch | Statement: [Econometrica, founder, Ragnar Frisch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ragnar Frisch Context triple: [Econometrica, founder, Ragnar Frisch]
-
A.
Ragnar Frisch
chosen
Ragnar Frisch was a Norwegian economist and co-recipient of the first Nobel Memorial Prize in Economic Sciences, recognized as a founder of econometrics and modern macroeconomic analysis.
-
B.
Trygve Haavelmo
Trygve Haavelmo was a Norwegian economist and Nobel laureate renowned for his pioneering work in econometrics and the probabilistic foundations of economic theory.
-
C.
Jan Tinbergen
Jan Tinbergen was a Dutch economist and Nobel laureate renowned as a pioneer of econometrics and modern economic policy modeling.
-
D.
Tjalling C. Koopmans
Tjalling C. Koopmans was a Dutch-American economist and Nobel laureate renowned for his contributions to econometrics and optimal resource allocation theory.
-
E.
Finn E. Kydland
Finn E. Kydland is a Norwegian economist and Nobel laureate renowned for his work on time consistency in economic policy and the driving forces behind business cycles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5f1c9888190b2817138c6893cfe |
completed | March 1, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a64a618c248190ab1bcecba04d3da8 |
completed | March 3, 2026, 2:41 a.m. |
Created at: March 1, 2026, 7:37 p.m.