Triple

T3500935
Position Surface form Disambiguated ID Type / Status
Subject Certificate in Data Science E73964 entity
Predicate usesTool P98 FINISHED
Object R E98913 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: R | Statement: [Certificate in Data Science, usesTool, R]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: R
Context triple: [Certificate in Data Science, usesTool, R]
  • A. R
    R is a New York City Subway service that runs along the Broadway Line in Manhattan and Queens, providing local transit through key commercial and residential areas.
  • B. R chosen
    R is a widely used open-source programming language and environment focused on statistical computing, data analysis, and graphical visualization.
  • C. RA
    RA is the commonly used abbreviation for Rugby Australia, the governing body for rugby union in Australia.
  • D. RA
    RA is a prestigious post-nominal title indicating membership as a Royal Academician of the Royal Academy of Arts in London.
  • E. RA
    RA is the commonly used abbreviation for the Royal Regiment of Artillery, a principal artillery branch of the British Army.
  • 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_69ad85cdb6e48190a335d412b9194ed8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbd5fbe8819091b61fa8df355f0c completed March 8, 2026, 6:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373d88dc08190a8508f990b01cf03 completed March 13, 2026, 2:18 a.m.
Created at: March 8, 2026, 3:18 p.m.