Triple

T20106441
Position Surface form Disambiguated ID Type / Status
Subject Gemini Pro E490189 entity
Predicate brand P1500 FINISHED
Object Google Gemini 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: Google Gemini | Statement: [Gemini Pro, brand, Google Gemini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Google Gemini
Context triple: [Gemini Pro, brand, Google Gemini]
  • A. Google Gemini chosen
    Google Gemini is Google's family of advanced multimodal AI models designed to handle text, code, images, and other data types for a wide range of intelligent applications.
  • B. Google Assistant
    Google Assistant is Google's AI-powered virtual assistant that provides voice-activated help, information, and smart device control across phones, speakers, watches, and other connected devices.
  • C. Gemini 1.5
    Gemini 1.5 is an advanced version of Google’s Gemini AI model family, offering improved multimodal reasoning and performance over earlier releases.
  • D. Google AI Studio
    Google AI Studio is a web-based development environment from Google that lets developers build, test, and integrate applications using Gemini and other Google AI models.
  • E. 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.
  • 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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e666dcb8d4819091889e19dd9137a6 completed April 20, 2026, 5:48 p.m.
Created at: April 11, 2026, 11:28 p.m.