Triple
T14284317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Mechanical Engineering, Johns Hopkins University |
E354128
|
entity |
| Predicate | collaboratesWith |
P37
|
FINISHED |
| Object |
Laboratory for Computational Sensing and Robotics
The Laboratory for Computational Sensing and Robotics is a Johns Hopkins University research center focused on advancing robotics, computer vision, and sensing technologies for applications in medicine, industry, and autonomous systems.
|
E1090654
|
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: Laboratory for Computational Sensing and Robotics | Statement: [Department of Mechanical Engineering, Johns Hopkins University, collaboratesWith, Laboratory for Computational Sensing and Robotics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laboratory for Computational Sensing and Robotics Context triple: [Department of Mechanical Engineering, Johns Hopkins University, collaboratesWith, Laboratory for Computational Sensing and Robotics]
-
A.
General Robotics, Automation, Sensing and Perception Laboratory
The General Robotics, Automation, Sensing and Perception Laboratory is a leading University of Pennsylvania research lab focused on advancing robotics, computer vision, automation, and related fields.
-
B.
Field Robotics Center at Carnegie Mellon University
The Field Robotics Center at Carnegie Mellon University is a leading research institute specializing in the development of advanced autonomous robots for challenging and unstructured environments such as space, deep sea, and disaster zones.
-
C.
Center for Humans and Machines
The Center for Humans and Machines is a research unit that studies the interactions between humans and intelligent technologies, focusing on how digitalization and AI shape individual behavior and society.
-
D.
Institute for Robotics and Intelligent Machines
The Institute for Robotics and Intelligent Machines is a research center focused on advancing robotics, artificial intelligence, and autonomous systems through interdisciplinary collaboration.
-
E.
MIT Laboratory for Information and Decision Systems
The MIT Laboratory for Information and Decision Systems is a research laboratory at the Massachusetts Institute of Technology focused on advancing the theory and applications of systems, control, communications, and data science.
- 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: Laboratory for Computational Sensing and Robotics Triple: [Department of Mechanical Engineering, Johns Hopkins University, collaboratesWith, Laboratory for Computational Sensing and Robotics]
Generated description
The Laboratory for Computational Sensing and Robotics is a Johns Hopkins University research center focused on advancing robotics, computer vision, and sensing technologies for applications in medicine, industry, and autonomous systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laboratory for Computational Sensing and Robotics Target entity description: The Laboratory for Computational Sensing and Robotics is a Johns Hopkins University research center focused on advancing robotics, computer vision, and sensing technologies for applications in medicine, industry, and autonomous systems.
-
A.
General Robotics, Automation, Sensing and Perception Laboratory
The General Robotics, Automation, Sensing and Perception Laboratory is a leading University of Pennsylvania research lab focused on advancing robotics, computer vision, automation, and related fields.
-
B.
Field Robotics Center at Carnegie Mellon University
The Field Robotics Center at Carnegie Mellon University is a leading research institute specializing in the development of advanced autonomous robots for challenging and unstructured environments such as space, deep sea, and disaster zones.
-
C.
Center for Humans and Machines
The Center for Humans and Machines is a research unit that studies the interactions between humans and intelligent technologies, focusing on how digitalization and AI shape individual behavior and society.
-
D.
Institute for Robotics and Intelligent Machines
The Institute for Robotics and Intelligent Machines is a research center focused on advancing robotics, artificial intelligence, and autonomous systems through interdisciplinary collaboration.
-
E.
MIT Laboratory for Information and Decision Systems
The MIT Laboratory for Information and Decision Systems is a research laboratory at the Massachusetts Institute of Technology focused on advancing the theory and applications of systems, control, communications, and data science.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de697d9fd08190b0cd7a6a6737ba03 |
completed | April 14, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d1a6d8081908e857143c0c809c0 |
completed | May 8, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69fd3da6f0648190876dd86dd51e72cc |
completed | May 8, 2026, 1:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd3e30868481908b55b368ab45c7fb |
completed | May 8, 2026, 1:36 a.m. |
Created at: April 10, 2026, 1:10 a.m.