Triple

T21989488
Position Surface form Disambiguated ID Type / Status
Subject UDDI E543045 entity
Predicate initiallyDevelopedBy P32488 FINISHED
Object Ariba NE NERFINISHED

How this triple was built (2 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: Ariba | Statement: [UDDI, initiallyDevelopedBy, Ariba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ariba
Context triple: [UDDI, initiallyDevelopedBy, Ariba]
  • A. SAP
    SAP is the IATA airport code for Ramón Villeda Morales International Airport, the main air gateway serving San Pedro Sula, Honduras.
  • B. SAP
    SAP is the commonly used abbreviation for the Société d’Anthropologie de Paris, a French learned society dedicated to the study of anthropology.
  • C. SAP chosen
    SAP is a leading global enterprise software company best known for its ERP solutions that help organizations manage business operations and customer relations.
  • D. SAP
    SAP was the former official currency of South Africa, used before the adoption of the South African rand.
  • E. SAP
    SAP is the station code for Lisbon Santa Apolónia, one of the main railway terminals in Lisbon, Portugal.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c48136b081908831fa907cc02e18 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1270cb67c81909a3aa2dc61c1894f completed April 28, 2026, 9:30 p.m.
Created at: April 16, 2026, 8:05 p.m.