Triple

T9532657
Position Surface form Disambiguated ID Type / Status
Subject VMS E229932 entity
Predicate supportsProgrammingLanguage P1592 FINISHED
Object Ada E8676 NE FINISHED

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: Ada | Statement: [VMS, supportsProgrammingLanguage, Ada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ada
Context triple: [VMS, supportsProgrammingLanguage, Ada]
  • A. Ada
    Ada is the given name of Ada Yonath, the Nobel Prize–winning Israeli crystallographer renowned for her pioneering work on the structure of the ribosome.
  • B. Ada
    Ada is a small city in south-central Oklahoma known as the county seat of Pontotoc County and home to East Central University and the headquarters of the Chickasaw Nation.
  • C. Ada
    Ada is a coastal town and traditional Ga-Adangbe community in the Greater Accra Region of Ghana, known for its estuary, beaches, and cultural heritage.
  • D. Ada
    Ada is a town in northern Serbia's Vojvodina region, known for its Hungarian ethnic majority and location along the Tisa River.
  • E. Ada (programming language) chosen
    Ada is a statically typed, high-level programming language designed with strong support for reliability, safety, and real-time systems, widely used in mission-critical and embedded applications such as aerospace and defense.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8479934c81908006d0e6e970ae05 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98b5651881908241b040f123c6a8 completed April 1, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d15275e4c08190a8aeb02caff052d8 completed April 4, 2026, 6:03 p.m.
Created at: March 30, 2026, 8 p.m.