Triple
T16630498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicholas Metropolis |
E404064
|
entity |
| Predicate | coDeveloperOf |
P6901
|
FINISHED |
| Object | Metropolis–Hastings algorithm |
E260028
|
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: Metropolis–Hastings algorithm | Statement: [Nicholas Metropolis, coDeveloperOf, Metropolis–Hastings algorithm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metropolis–Hastings algorithm Context triple: [Nicholas Metropolis, coDeveloperOf, Metropolis–Hastings algorithm]
-
A.
Metropolis algorithm
chosen
The Metropolis algorithm is a foundational Markov chain Monte Carlo method used to sample from complex probability distributions by accepting or rejecting proposed moves according to a specific probabilistic rule.
-
B.
Gibbs sampling
Gibbs sampling is a Markov chain Monte Carlo algorithm that generates samples from complex multivariate probability distributions by iteratively sampling each variable from its conditional distribution given the others.
-
C.
Markov chain Monte Carlo
Markov chain Monte Carlo is a class of algorithms that uses Markov chains to generate samples from complex probability distributions, widely used in Bayesian inference, statistical physics, and machine learning.
-
D.
Hamiltonian Monte Carlo
Hamiltonian Monte Carlo is an advanced Markov chain Monte Carlo sampling algorithm that uses concepts from Hamiltonian dynamics to efficiently explore complex, high-dimensional probability distributions.
-
E.
The Metropolis Ensemble
The Metropolis Ensemble is a New York–based contemporary chamber orchestra known for innovative collaborations and performances of new and experimental classical music.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e4db5081908a6085f1bc2d65b8 |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084b7b94481909dfc0dd7b009a5b4 |
completed | May 10, 2026, 1:14 p.m. |
Created at: April 10, 2026, 5:17 a.m.