Triple

T18008340
Position Surface form Disambiguated ID Type / Status
Subject OpenAI API platform E430811 entity
Predicate supportsUseCase P203 FINISHED
Object RAG (retrieval-augmented generation) — 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: RAG (retrieval-augmented generation) | Statement: [OpenAI API platform, supportsUseCase, RAG (retrieval-augmented generation)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RAG (retrieval-augmented generation)
Context triple: [OpenAI API platform, supportsUseCase, RAG (retrieval-augmented generation)]
  • A. RAG chosen
    RAG is the commonly used abbreviation for the Royal Galician Academy, the principal institution dedicated to the study and promotion of the Galician language and culture.
  • B. LLM
    LLM (Large Language Model) is an advanced artificial intelligence system trained on vast text datasets to understand and generate human-like language for a wide range of tasks.
  • C. LLM
    LLM is the ICAO airline designator assigned to Yamal Airlines, a Russian regional carrier.
  • D. PaLM 2
    PaLM 2 is a large-scale language model developed by Google, known for powering various AI features across Google products before being succeeded by the Gemini family of models.
  • E. GPT-3
    GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
  • 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b51d44088190bfcd35e532a4c02a completed April 19, 2026, 10:57 a.m.
Created at: April 10, 2026, 10:24 a.m.