Triple

T4650850
Position Surface form Disambiguated ID Type / Status
Subject Probabilistic Robotics E102290 entity
Predicate topic P261 FINISHED
Object Monte Carlo localization
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.
E457844 NE FINISHED

How this triple was built (4 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: [Probabilistic Robotics, topic, Monte Carlo localization]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monte Carlo localization
Context triple: [Probabilistic Robotics, topic, Monte Carlo localization]
  • A. SLAM
    SLAM is a major art museum in St. Louis, Missouri, renowned for its extensive collection spanning thousands of years and diverse cultures.
  • B. CMU Highly Intelligent Mobile Platform
    CMU Highly Intelligent Mobile Platform (CHIMP) is a sophisticated humanoid robot developed at Carnegie Mellon University for advanced mobility, manipulation, and autonomous operation in challenging environments.
  • C. book "Probabilistic Robotics"
    "Probabilistic Robotics" is a foundational textbook that systematically introduces probabilistic methods for perception, localization, and control in mobile robotics.
  • D. Learning to See by Moving
    "Learning to See by Moving" is a research work in computer vision that explores how visual understanding can emerge from an agent’s own movement and interaction with the environment, rather than from static images alone.
  • E. Technical Committee on Mobile Robots
    The Technical Committee on Mobile Robots is a specialized IEEE Robotics and Automation Society group that advances research, standards, and collaboration in autonomous and mobile robotics.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Monte Carlo localization
Triple: [Probabilistic Robotics, topic, Monte Carlo localization]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Monte Carlo localization
Target entity description: 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.
  • A. SLAM
    SLAM is a major art museum in St. Louis, Missouri, renowned for its extensive collection spanning thousands of years and diverse cultures.
  • B. CMU Highly Intelligent Mobile Platform
    CMU Highly Intelligent Mobile Platform (CHIMP) is a sophisticated humanoid robot developed at Carnegie Mellon University for advanced mobility, manipulation, and autonomous operation in challenging environments.
  • C. book "Probabilistic Robotics"
    "Probabilistic Robotics" is a foundational textbook that systematically introduces probabilistic methods for perception, localization, and control in mobile robotics.
  • D. Learning to See by Moving
    "Learning to See by Moving" is a research work in computer vision that explores how visual understanding can emerge from an agent’s own movement and interaction with the environment, rather than from static images alone.
  • E. Technical Committee on Mobile Robots
    The Technical Committee on Mobile Robots is a specialized IEEE Robotics and Automation Society group that advances research, standards, and collaboration in autonomous and mobile robotics.
  • F. None of above. chosen

Provenance (5 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_69bd43d71a308190afea7280841b0de8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6302078081909451589d39c7b28c completed March 20, 2026, 3:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfae7636881908244b86cba1c66b7 completed March 21, 2026, 1:56 a.m.
NEDg Description generation batch_69bdfbc12acc8190b8116a6003abb3e3 completed March 21, 2026, 2 a.m.
NED2 Entity disambiguation (via description) batch_69bdfc44536c8190a71e52b0690a7570 completed March 21, 2026, 2:02 a.m.
Created at: March 20, 2026, 1:14 p.m.