Triple

T7196446
Position Surface form Disambiguated ID Type / Status
Subject OWL 2 RL E168626 entity
Predicate contrastedWith P278 FINISHED
Object 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.
E657899 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: OWL 2 DL | Statement: [OWL 2 RL, contrastedWith, OWL 2 DL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OWL 2 DL
Context triple: [OWL 2 RL, contrastedWith, OWL 2 DL]
  • A. 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.
  • 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 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.
  • D. 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.
  • E. OWL DL
    OWL DL is a sublanguage of the Web Ontology Language that balances expressive power with computational decidability by adhering closely to description logic foundations.
  • 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: OWL 2 DL
Triple: [OWL 2 RL, contrastedWith, OWL 2 DL]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: OWL 2 DL
Target entity description: 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.
  • A. 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.
  • 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 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.
  • D. 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.
  • E. OWL DL
    OWL DL is a sublanguage of the Web Ontology Language that balances expressive power with computational decidability by adhering closely to description logic foundations.
  • 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_69c68a5376748190bb500f03df86e93e completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6e928ecdc8190a7f3feaf6d28781b completed March 27, 2026, 8:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa67ec208190b513bf7e8252cdcb completed March 28, 2026, 3:57 p.m.
NEDg Description generation batch_69c7fbe2a86881909be54dac809aa9af completed March 28, 2026, 4:03 p.m.
NED2 Entity disambiguation (via description) batch_69c7fc84fff48190b4b43da21a9ede51 completed March 28, 2026, 4:06 p.m.
Created at: March 27, 2026, 2:51 p.m.