Triple

T5052827
Position Surface form Disambiguated ID Type / Status
Subject Google Gemini E113825 entity
Predicate competitor P1375 FINISHED
Object OpenAI GPT-4 E19435 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: OpenAI GPT-4 | Statement: [Google Gemini, competitor, OpenAI GPT-4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OpenAI GPT-4
Context triple: [Google Gemini, competitor, OpenAI GPT-4]
  • A. GPT-4 chosen
    GPT-4 is a large multimodal language model known for its advanced reasoning, comprehension, and generation capabilities across text and images.
  • B. GPT-4o
    GPT-4o is an advanced multimodal large language model in the GPT series capable of understanding and generating text, images, and other data types with high efficiency.
  • C. 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.
  • D. ChatGPT
    ChatGPT is an advanced conversational AI model developed by OpenAI that can understand and generate human-like text across a wide range of topics and tasks.
  • E. OpenAI API platform
    The OpenAI API platform is a cloud-based service that provides developers with programmatic access to OpenAI’s language, code, and other AI models for integration into applications and workflows.
  • 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_69bd443aa1f88190abb992d138f2cf42 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7428d7a88190b990aedae390acbe completed March 20, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea486b394819082ea80694843b29e completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:38 p.m.