Triple

T13193699
Position Surface form Disambiguated ID Type / Status
Subject Ralf Baader E314055 entity
Predicate authorOf P4244 FINISHED
Object The Description Logic Handbook
The Description Logic Handbook is a comprehensive reference work on description logics, covering their theory, implementation, and applications in knowledge representation and reasoning.
E1027658 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: The Description Logic Handbook | Statement: [Ralf Baader, authorOf, The Description Logic Handbook]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Description Logic Handbook
Context triple: [Ralf Baader, authorOf, The Description Logic Handbook]
  • A. OWL 2 RL
    OWL 2 RL is a profile of the Web Ontology Language designed for scalable reasoning using rule-based systems, enabling efficient inference over large datasets.
  • B. OWL 2 EL
    OWL 2 EL is a lightweight profile of the Web Ontology Language designed for efficient reasoning over large-scale ontologies, particularly in domains like biomedical terminologies.
  • C. OWL 2 DL
    OWL 2 DL is a highly expressive yet decidable description logic–based profile of the OWL 2 Web Ontology Language, designed to balance rich modeling capabilities with computational completeness and decidability.
  • D. OWL 2 Full
    OWL 2 Full is a highly expressive semantic web ontology language variant that fully integrates OWL with RDF, allowing powerful but undecidable reasoning over web data.
  • E. OWL 2 Web Ontology Language
    OWL 2 Web Ontology Language is a W3C-standardized knowledge representation language used to create, share, and reason over rich ontologies on the Semantic Web.
  • 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: The Description Logic Handbook
Triple: [Ralf Baader, authorOf, The Description Logic Handbook]
Generated description
The Description Logic Handbook is a comprehensive reference work on description logics, covering their theory, implementation, and applications in knowledge representation and reasoning.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: The Description Logic Handbook
Target entity description: The Description Logic Handbook is a comprehensive reference work on description logics, covering their theory, implementation, and applications in knowledge representation and reasoning.
  • A. OWL 2 RL
    OWL 2 RL is a profile of the Web Ontology Language designed for scalable reasoning using rule-based systems, enabling efficient inference over large datasets.
  • B. OWL 2 EL
    OWL 2 EL is a lightweight profile of the Web Ontology Language designed for efficient reasoning over large-scale ontologies, particularly in domains like biomedical terminologies.
  • C. OWL 2 DL
    OWL 2 DL is a highly expressive yet decidable description logic–based profile of the OWL 2 Web Ontology Language, designed to balance rich modeling capabilities with computational completeness and decidability.
  • D. OWL 2 Full
    OWL 2 Full is a highly expressive semantic web ontology language variant that fully integrates OWL with RDF, allowing powerful but undecidable reasoning over web data.
  • E. OWL 2 Web Ontology Language
    OWL 2 Web Ontology Language is a W3C-standardized knowledge representation language used to create, share, and reason over rich ontologies on the Semantic Web.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c6158e4819082c8ad75b4dfdd90 completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f600f7a08190bcdd80d5563517c3 completed May 3, 2026, 7:15 a.m.
NEDg Description generation batch_69f6fa2e76fc819095f9a7e83189283c completed May 3, 2026, 7:33 a.m.
NED2 Entity disambiguation (via description) batch_69f6fb52f82c81909dcec658c7f58ec7 completed May 3, 2026, 7:37 a.m.
Created at: April 9, 2026, 9:16 p.m.