Triple

T19434880
Position Surface form Disambiguated ID Type / Status
Subject WebLogic Domain E486202 entity
Predicate introducedBy P513 FINISHED
Object BEA Systems 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: BEA Systems | Statement: [WebLogic Domain, introducedBy, BEA Systems]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BEA Systems
Context triple: [WebLogic Domain, introducedBy, BEA Systems]
  • A. BEA Systems chosen
    BEA Systems was a software company best known for its enterprise middleware and application server products that played a major role in early Java-based web and enterprise computing.
  • B. BEA
    BEA is a U.S. government agency that produces key economic statistics, including measures of national income, output, and growth.
  • C. BEA
    BEA is the French Bureau of Enquiry and Analysis for Civil Aviation Safety, the government agency responsible for investigating civil aviation accidents and incidents.
  • D. BEA
    BEA is the abbreviation commonly used for the British Electricity Authority, the former nationalized body responsible for electricity generation and transmission in post-war Britain.
  • E. BEA
    BEA was the acronym for British European Airways, a former UK state-owned airline that operated primarily short- and medium-haul routes across Europe before merging into British Airways.
  • 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6335e8f7881909c8b28886521046e completed April 20, 2026, 2:08 p.m.
Created at: April 10, 2026, 1:37 p.m.