Neurosymbolic Graph Enrichment for Grounded World Models | Paper Citation Record

Observation b01307c0-6102-4605-8a3e-4caf6ced4079 · outbound

This paper cites LLM-assisted knowledge graph engineering: Experiments with ChatGPT,.

Neurosymbolic Graph Enrichment for Grounded World Models LLM-assisted knowledge graph engineering: Experiments with ChatGPT,

Reference 1

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Observation c5d04287-0524-42d3-b910-8e248df7d447 · outbound

This paper cites Identifying motifs for evaluating open knowledge extraction on the Web,.

Neurosymbolic Graph Enrichment for Grounded World Models Identifying motifs for evaluating open knowledge extraction on the Web,

Reference 2

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Observation ff7eee2c-cb5a-4f02-adce-2c846116ed8d · outbound

This paper cites LLMs for knowledge graph construction and reasoning: Recent capabilities and future opportunities,.

Neurosymbolic Graph Enrichment for Grounded World Models LLMs for knowledge graph construction and reasoning: Recent capabilities and future opportunities,

Reference 3

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Observation d8c2fb0e-6f7f-4838-8aa8-6db39fc3083b · outbound

This paper cites Knowledge graph-augmented lan- guage models for complex question answering,.

Neurosymbolic Graph Enrichment for Grounded World Models Knowledge graph-augmented lan- guage models for complex question answering,

Reference 4

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Observation 489fe77a-5d9b-4348-978f-cc73a0ecbd44 · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

Neurosymbolic Graph Enrichment for Grounded World Models From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 5

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Observation 731a7723-011b-4e28-acbe-597a5fdd0d05 · outbound

This paper cites KG-BERT: BERT for Knowledge Graph Completion.

Neurosymbolic Graph Enrichment for Grounded World Models KG-BERT: BERT for Knowledge Graph Completion

Reference 6

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Observation cf8e6680-2cac-4356-a23a-7624cdeb2cdb · outbound

This paper cites Utilizing textual information in knowledge graph embedding: A survey of methods and applications,.

Neurosymbolic Graph Enrichment for Grounded World Models Utilizing textual information in knowledge graph embedding: A survey of methods and applications,

Reference 7

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Observation df623ce8-9e9d-4169-97e0-0391b950d143 · outbound

This paper cites Preface for the International Work- shop on Knowledge Graph Generation from Text,.

Neurosymbolic Graph Enrichment for Grounded World Models Preface for the International Work- shop on Knowledge Graph Generation from Text,

Reference 8

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Observation 8ffcdb8f-f274-43b2-92ce-a3e10dc67062 · outbound

This paper cites Oops!(ontology pitfall scanner!): An on-line tool for ontology evalua- tion,.

Neurosymbolic Graph Enrichment for Grounded World Models Oops!(ontology pitfall scanner!): An on-line tool for ontology evalua- tion,

Reference 9

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This paper cites NeOn-GPT: A Large Language Model-Powered Pipeline for Ontology Learning,.

Neurosymbolic Graph Enrichment for Grounded World Models NeOn-GPT: A Large Language Model-Powered Pipeline for Ontology Learning,

Reference 10

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Observation 8e2cd951-3627-4709-bc69-57a2da0fbf95 · outbound

This paper cites HermiT: an OWL 2 reasoner,.

Neurosymbolic Graph Enrichment for Grounded World Models HermiT: an OWL 2 reasoner,

Reference 11

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Observation 86e5b48b-eca5-4081-9242-d5a76ceebece · outbound

This paper cites Serving DBpedia with DOLCE–more than just adding a cherry on top,.

Neurosymbolic Graph Enrichment for Grounded World Models Serving DBpedia with DOLCE–more than just adding a cherry on top,

Reference 12

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Observation d29cc8e2-aeee-48c2-ab90-1603eccd2046 · outbound

This paper cites One SPRING to rule them both: Symmetric AMR semantic parsing and generation without a com- plex pipeline,.

Neurosymbolic Graph Enrichment for Grounded World Models One SPRING to rule them both: Symmetric AMR semantic parsing and generation without a com- plex pipeline,

Reference 13

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Observation 737b37c0-d2a1-4e1c-8bb1-53d2b5dbd390 · outbound

This paper cites Scalable Zero-shot Entity Linking with Dense Entity Retrieval.

Neurosymbolic Graph Enrichment for Grounded World Models Scalable Zero-shot Entity Linking with Dense Entity Retrieval

Reference 14

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Observation e032ec3c-ed79-4669-b4b2-b23a38374ac6 · outbound

This paper cites AMR2FRED, a tool for translating abstract meaning representation to motif-based linguistic knowledge graphs,.

Neurosymbolic Graph Enrichment for Grounded World Models AMR2FRED, a tool for translating abstract meaning representation to motif-based linguistic knowledge graphs,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.690633Z

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Observation 45b54158-97b2-4d18-a5e3-b0b9a01352e5 · outbound

This paper cites Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incor- porating Knowledge Graph Information,.

Neurosymbolic Graph Enrichment for Grounded World Models Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incor- porating Knowledge Graph Information,

Reference 16

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Observation ad6b0065-e446-4b38-9bd3-1c42225a54d6 · outbound

This paper cites Is neuro-symbolic ai meeting its promises in natural language processing? a structured re- view,.

Neurosymbolic Graph Enrichment for Grounded World Models Is neuro-symbolic ai meeting its promises in natural language processing? a structured re- view,

Reference 17

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This paper cites The third ai summer: AAAI robert s. engelmore memorial lecture,.

Neurosymbolic Graph Enrichment for Grounded World Models The third ai summer: AAAI robert s. engelmore memorial lecture,

Reference 18

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Observation 8dd41828-2ea2-4135-b0d9-6e606722b6ca · outbound

This paper cites Framester: A wide coverage linguistic linked data hub,.

Neurosymbolic Graph Enrichment for Grounded World Models Framester: A wide coverage linguistic linked data hub,

Reference 19

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Observation 257333f7-6ff1-42ba-a867-ecf656d2462f · outbound

This paper cites Symbolic logic meets machine learning: A brief survey in infinite domains,.

Neurosymbolic Graph Enrichment for Grounded World Models Symbolic logic meets machine learning: A brief survey in infinite domains,

Reference 20

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Observation 374a6a5e-7a89-4dbf-b465-73d1571a029e · outbound

This paper cites Neural-symbolic learning and reasoning: A survey 30 and interpretation 1,.

Neurosymbolic Graph Enrichment for Grounded World Models Neural-symbolic learning and reasoning: A survey 30 and interpretation 1,

Reference 21

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This paper cites Neurosymbolic AI: The 3rd wave,.

Neurosymbolic Graph Enrichment for Grounded World Models Neurosymbolic AI: The 3rd wave,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.440374Z

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This paper cites Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective.

Neurosymbolic Graph Enrichment for Grounded World Models Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective

Reference 23

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Observation 176e8a6e-bdf1-461d-bd30-bff323b6b904 · outbound

This paper cites Neuro-symbolic ar- tificial intelligence,.

Neurosymbolic Graph Enrichment for Grounded World Models Neuro-symbolic ar- tificial intelligence,

Reference 24

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This paper cites Learning to activate logic rules for textual reasoning,.

Neurosymbolic Graph Enrichment for Grounded World Models Learning to activate logic rules for textual reasoning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.348919Z

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Observation c642ba17-9b26-4bd5-968f-b43766520eab · outbound

This paper cites A survey on neural- symbolic learning systems,.

Neurosymbolic Graph Enrichment for Grounded World Models A survey on neural- symbolic learning systems,

Reference 26

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Observation 0a700670-c14a-497e-b9d0-27cbe8c3c186 · outbound

This paper cites Neural, symbolic and neural-symbolic reasoning on knowledge graphs,.

Neurosymbolic Graph Enrichment for Grounded World Models Neural, symbolic and neural-symbolic reasoning on knowledge graphs,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.276269Z

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Observation 22cbd113-7265-42b2-a4a6-dc4eeb81ea5b · outbound

This paper cites What’s in a concept: structural foundations for se- mantic networks,.

Neurosymbolic Graph Enrichment for Grounded World Models What’s in a concept: structural foundations for se- mantic networks,

Reference 28

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Observation e4e60b3e-0d0a-42a7-a3a1-6691327da760 · outbound

This paper cites A framework for representing knowledge,.

Neurosymbolic Graph Enrichment for Grounded World Models A framework for representing knowledge,

Reference 29

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Observation 81cb4dd9-02c7-4aba-bbc4-53c97d50ac13 · outbound

This paper cites Frame semantics,.

Neurosymbolic Graph Enrichment for Grounded World Models Frame semantics,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.182874Z

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Observation 2a6b6609-e2ad-4b6f-b6ad-34df3c34bb97 · outbound

This paper cites Neurosymbolic Methods for Dynamic Knowledge Graphs.

Neurosymbolic Graph Enrichment for Grounded World Models Neurosymbolic Methods for Dynamic Knowledge Graphs

Reference 31

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Observation 013bba6a-1138-453f-9c57-cc9730e26b74 · outbound

This paper cites Closing the Loop between knowledge patterns in cogni- tion and the Semantic Web,.

Neurosymbolic Graph Enrichment for Grounded World Models Closing the Loop between knowledge patterns in cogni- tion and the Semantic Web,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.152444Z

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Observation a01e41cc-474f-4b11-b62b-6fd271e60c05 · outbound

This paper cites WordNet: An electronic lexical database,.

Neurosymbolic Graph Enrichment for Grounded World Models WordNet: An electronic lexical database,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.113857Z

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Observation 438ca7d6-ec60-42a8-b013-c27c2ea78939 · outbound

This paper cites VerbNet: A broad-coverage, comprehensive verb lexi- con,.

Neurosymbolic Graph Enrichment for Grounded World Models VerbNet: A broad-coverage, comprehensive verb lexi- con,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.082386Z

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Observation 7bc7c194-fbf4-425c-8e56-fb5399c66a4c · outbound

This paper cites Amnestic Forgery: An Ontology of Conceptual Metaphors,.

Neurosymbolic Graph Enrichment for Grounded World Models Amnestic Forgery: An Ontology of Conceptual Metaphors,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.036900Z

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Observation ac884c4a-dd46-41ef-be57-5fb07d2a360f · outbound

This paper cites Imageschemanet: Formal- izing embodied commonsense knowledge providing an imageschematic layer to framester,.

Neurosymbolic Graph Enrichment for Grounded World Models Imageschemanet: Formal- izing embodied commonsense knowledge providing an imageschematic layer to framester,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:53.008551Z

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Observation b14ac989-5ab3-4eba-a94a-3f4a820a945d · outbound

This paper cites BabelNet: Building a very large multilin- gual semantic network,.

Neurosymbolic Graph Enrichment for Grounded World Models BabelNet: Building a very large multilin- gual semantic network,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.983381Z

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Observation b939f15c-e471-48b4-b0c7-bba60e812767 · outbound

This paper cites Dbpedia: A nucleus for a web of open data,.

Neurosymbolic Graph Enrichment for Grounded World Models Dbpedia: A nucleus for a web of open data,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.961076Z

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This paper cites Yago: a core of seman- tic knowledge,.

Neurosymbolic Graph Enrichment for Grounded World Models Yago: a core of seman- tic knowledge,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.939874Z

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This paper cites Sweetening wordnet with dolce,.

Neurosymbolic Graph Enrichment for Grounded World Models Sweetening wordnet with dolce,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.895028Z

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Observation 77fec279-e14b-400e-88fb-aa6746fca680 · outbound

This paper cites Unifying large language models and knowledge graphs: A roadmap,.

Neurosymbolic Graph Enrichment for Grounded World Models Unifying large language models and knowledge graphs: A roadmap,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.865162Z

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This paper cites Semantic web machine reading with FRED,.

Neurosymbolic Graph Enrichment for Grounded World Models Semantic web machine reading with FRED,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.837696Z

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Observation f98c214f-aa08-47dc-aa74-ca3b5dfb7c7c · outbound

This paper cites The berkeley framenet project,.

Neurosymbolic Graph Enrichment for Grounded World Models The berkeley framenet project,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.805423Z

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Observation e83fa77d-68bb-4b82-adec-a02a73ce7b2b · outbound

This paper cites From TreeBank to PropBank,.

Neurosymbolic Graph Enrichment for Grounded World Models From TreeBank to PropBank,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.765017Z

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Observation d6bd0177-c125-4839-844a-0aa5155bf306 · outbound

This paper cites Presupposition: What went wrong?,.

Neurosymbolic Graph Enrichment for Grounded World Models Presupposition: What went wrong?,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.722091Z

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This paper cites On sense and reference,.

Neurosymbolic Graph Enrichment for Grounded World Models On sense and reference,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.692472Z

Source-reported events for the cited work

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This paper cites On referring,.

Neurosymbolic Graph Enrichment for Grounded World Models On referring,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.657830Z

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Observation f8361d8a-123e-480b-8391-5cdd159d04f8 · outbound

This paper cites Logic and conversation,.

Neurosymbolic Graph Enrichment for Grounded World Models Logic and conversation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.617718Z

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Observation 5a75f900-9eb8-433b-99bd-acaa2cf2fce1 · outbound

This paper cites Presumptive meanings: The theory of generalized con- versational implicature,.

Neurosymbolic Graph Enrichment for Grounded World Models Presumptive meanings: The theory of generalized con- versational implicature,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.581316Z

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Observation 2fa3268f-6368-4082-9eda-85400c553023 · outbound

This paper cites Article commentary: Judgment and decision making: A personal view,.

Neurosymbolic Graph Enrichment for Grounded World Models Article commentary: Judgment and decision making: A personal view,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.536029Z

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Observation 4350e322-516b-4f00-ae32-e44d7167fde1 · outbound

This paper cites The Body in the Mind: The Bodily Basis of Meaning, Imagination, and Reason,.

Neurosymbolic Graph Enrichment for Grounded World Models The Body in the Mind: The Bodily Basis of Meaning, Imagination, and Reason,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.499902Z

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Observation 8b21e744-1ccd-4d06-b840-a3e65f1569ff · outbound

This paper cites Metaphors we live by,.

Neurosymbolic Graph Enrichment for Grounded World Models Metaphors we live by,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.475818Z

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Observation 35966585-6561-4f95-818d-0cf31d9daf3e · outbound

This paper cites Philosophy in the flesh: The embodied mind and its challenge to western thought,.

Neurosymbolic Graph Enrichment for Grounded World Models Philosophy in the flesh: The embodied mind and its challenge to western thought,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.442533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 41badd60-29cb-4b14-8967-00f0f1cdc226 · outbound

This paper cites A narrative in three acts: Using combinations of image schemas to model events,.

Neurosymbolic Graph Enrichment for Grounded World Models A narrative in three acts: Using combinations of image schemas to model events,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.397618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 82a5bb5e-d5b6-4fd8-b2af-d82c6861b442 · outbound

This paper cites Image schemas and concept invention: cognitive, log- ical, and linguistic investigations,.

Neurosymbolic Graph Enrichment for Grounded World Models Image schemas and concept invention: cognitive, log- ical, and linguistic investigations,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.349876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9713069e-1c6f-4965-add5-9854e3b4ac0e · outbound

This paper cites ChainNet: Structured Metaphor and Metonymy in WordNet.

Neurosymbolic Graph Enrichment for Grounded World Models ChainNet: Structured Metaphor and Metonymy in WordNet

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-12T17:19:51.660488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8f06aef4-e384-4dc2-8911-f029dca42f76 · outbound

This paper cites Moral foundations theory: The pragmatic validity of moral pluralism,.

Neurosymbolic Graph Enrichment for Grounded World Models Moral foundations theory: The pragmatic validity of moral pluralism,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.302055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation da8bd103-6e45-4139-a54a-d6575c49f5c3 · outbound

This paper cites The CAD triad hypothesis: a mapping between three moral emotions (contempt, anger, disgust) and three moral codes (community, autonomy, divinity),.

Neurosymbolic Graph Enrichment for Grounded World Models The CAD triad hypothesis: a mapping between three moral emotions (contempt, anger, disgust) and three moral codes (community, autonomy, divinity),

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.259186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a1787499-d99e-46cd-b6e0-f911f624aea2 · outbound

This paper cites Extending the cross-cultural validity of the theory of ba- sic human values with a different method of measurement,.

Neurosymbolic Graph Enrichment for Grounded World Models Extending the cross-cultural validity of the theory of ba- sic human values with a different method of measurement,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.224777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dad74178-a58a-4aa5-8482-2fb6fd78cd80 · outbound

This paper cites Logic as semiotic: The theory of signs,.

Neurosymbolic Graph Enrichment for Grounded World Models Logic as semiotic: The theory of signs,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.190057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8846b849-e6f3-431a-abd7-d138d94fb645 · outbound

This paper cites Hamlet and his problems,.

Neurosymbolic Graph Enrichment for Grounded World Models Hamlet and his problems,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.161155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 42e6a412-60cd-44a3-8ace-44a9e9f37092 · outbound

This paper cites Counterintuitive behavior of social systems,.

Neurosymbolic Graph Enrichment for Grounded World Models Counterintuitive behavior of social systems,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.116526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b7477803-31c4-4b9d-b372-f7fbc7e941d6 · outbound

This paper cites Text2AMR2FRED, a Tool for Transforming Text into RDF/OWL Knowledge Graphs via Abstract Meaning Representation,.

Neurosymbolic Graph Enrichment for Grounded World Models Text2AMR2FRED, a Tool for Transforming Text into RDF/OWL Knowledge Graphs via Abstract Meaning Representation,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.089416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8b8062d8-fcd6-44ee-9e71-1d35b629f7d1 · outbound

This paper cites World Models.

Neurosymbolic Graph Enrichment for Grounded World Models World Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-12T17:19:51.458498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25600746-e1ea-43cf-a354-c10a2291ec71 · outbound

This paper cites On the unexpected abilities of large language models,.

Neurosymbolic Graph Enrichment for Grounded World Models On the unexpected abilities of large language models,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:52.044360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7b122487-0a7f-4682-8595-26116ee09596 · outbound

This paper cites Categorial and categorical grammars,.

Neurosymbolic Graph Enrichment for Grounded World Models Categorial and categorical grammars,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:51.987043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4fa40530-e1c0-4124-8a3e-27a611cc5e17 · outbound

This paper cites Wide-coverage semantic analysis with boxer,.

Neurosymbolic Graph Enrichment for Grounded World Models Wide-coverage semantic analysis with boxer,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:51.957043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 84689078-536c-47d1-a503-94ea153fc0b1 · outbound

This paper cites OWL 2: The next step for OWL,.

Neurosymbolic Graph Enrichment for Grounded World Models OWL 2: The next step for OWL,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:51.924898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 009c9676-37d6-4704-ab57-5e78d292f06d · outbound

This paper cites Basic human values and moral foundations theory in valuenet ontology,.

Neurosymbolic Graph Enrichment for Grounded World Models Basic human values and moral foundations theory in valuenet ontology,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:51.898603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8bcc8372-6be0-4c91-88b6-83f1dcdb98df · outbound

This paper cites Qlever: A query engine for efficient sparql+ text search,.

Neurosymbolic Graph Enrichment for Grounded World Models Qlever: A query engine for efficient sparql+ text search,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:19:51.866801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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