Triple
T15313026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AI2-THOR |
E366086
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | embodied AI benchmark |
C13033
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: embodied AI benchmark Context triple: [AI2-THOR, instanceOf, embodied AI benchmark]
-
A.
benchmark in artificial intelligence
chosen
A benchmark in artificial intelligence is a standardized task, dataset, or evaluation protocol used to quantitatively compare and assess the performance of AI models and algorithms.
-
B.
disembodied intelligence
A disembodied intelligence is a non-physical, self-aware cognitive entity that exists and operates independently of any biological or material body.
-
C.
test of machine intelligence
A test of machine intelligence is a systematic procedure or set of tasks designed to evaluate a machine's ability to exhibit behaviors or problem-solving capabilities that are typically associated with human cognitive processes.
-
D.
multimodal large language model family
A multimodal large language model family is a group of related neural models that can jointly process and generate multiple data modalities—such as text, images, audio, or video—using shared architectures, training objectives, and parameterizations.
-
E.
behavior-based robotics paradigm
The behavior-based robotics paradigm is an approach to robot control that builds complex, adaptive behavior from the interaction and coordination of many simple, decentralized behavior modules directly coupled to sensors and actuators, rather than relying on centralized symbolic planning.
- F. None of above.
Provenance (1 batch)
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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
Created at: April 10, 2026, 3:16 a.m.