Triple
T18723693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Markov localization |
E457843
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Monte Carlo localization |
—
|
NE NERFINISHED |
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: Monte Carlo localization | Statement: [Markov localization, relatedTo, Monte Carlo localization]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monte Carlo localization Context triple: [Markov localization, relatedTo, Monte Carlo localization]
-
A.
Monte Carlo localization
chosen
Monte Carlo localization is a probabilistic robotics algorithm that uses particle filters to estimate a robot’s pose within a known map based on noisy sensor and motion data.
-
B.
Markov localization
Markov localization is a probabilistic method in robotics for estimating a robot’s position by maintaining and updating a belief distribution over all possible locations based on sensor data and motion.
-
C.
Sequential Monte Carlo Methods for Bayesian Filtering
"Sequential Monte Carlo Methods for Bayesian Filtering" is a scholarly work that develops and analyzes particle filtering techniques for performing Bayesian inference in dynamic systems.
-
D.
SLAM
SLAM is a major art museum in St. Louis, Missouri, renowned for its extensive collection spanning thousands of years and diverse cultures.
-
E.
SLAM
SLAM (Simultaneous Localization and Mapping) is a computational technique in robotics and computer vision that enables a device to build a map of an unknown environment while simultaneously estimating its own position within that map.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56abcfc048190a01dee959e768768 |
completed | April 19, 2026, 11:52 p.m. |
Created at: April 10, 2026, 11:50 a.m.