Triple
T9062821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcus Hutter |
E217168
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Kolmogorov complexity |
E183589
|
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: Kolmogorov complexity | Statement: [Marcus Hutter, basedOn, Kolmogorov complexity]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kolmogorov complexity Context triple: [Marcus Hutter, basedOn, Kolmogorov complexity]
-
A.
Kolmogorov complexity
chosen
Kolmogorov complexity is a measure of the amount of information in an object, defined as the length of the shortest computer program that can produce it.
-
B.
Blum complexity measures
Blum complexity measures are a formal framework in computational complexity theory that rigorously define and compare the resource usage (such as time or space) of algorithms via axiomatic conditions.
-
C.
Martin-Löf randomness
Martin-Löf randomness is a rigorous mathematical notion of randomness for infinite binary sequences, defined via effectively null sets and closely connected to algorithmic information theory.
-
D.
Turing degrees
Turing degrees are an abstract classification of sets of natural numbers or decision problems according to their relative level of algorithmic unsolvability or computational complexity under Turing reducibility.
-
E.
Turing reducibility
Turing reducibility is a central computability-theoretic notion that compares the relative computational difficulty of decision problems by allowing one problem to be solved using an oracle for another.
- 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7ecd352c8190a744579209b2e535 |
completed | April 1, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfebf4b9348190a7f01c64098c25f7 |
completed | April 3, 2026, 4:33 p.m. |
Created at: March 30, 2026, 7:11 p.m.