Triple

T5052819
Position Surface form Disambiguated ID Type / Status
Subject Google Gemini E113825 entity
Predicate availableVia P9675 FINISHED
Object Vertex AI E97118 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: Vertex AI | Statement: [Google Gemini, availableVia, Vertex AI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vertex AI
Context triple: [Google Gemini, availableVia, Vertex AI]
  • A. Vertex AI chosen
    Vertex AI is Google Cloud’s unified machine learning platform for building, training, and deploying ML models at scale.
  • B. Landing AI
    Landing AI is a technology company focused on making artificial intelligence accessible to traditional industries by helping them build and deploy practical AI solutions, particularly in manufacturing and computer vision.
  • C. 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.
  • D. AI2
    AI2 is a research institute founded by Paul Allen that advances artificial intelligence through open science, impactful AI systems, and large-scale scholarly resources.
  • E. Oracle AI Services
    Oracle AI Services is a suite of cloud-based artificial intelligence tools and APIs from Oracle that enable developers to easily add capabilities like machine learning, computer vision, language processing, and anomaly detection to their applications.
  • 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_69beb0fd25c081909ddf2d8eb77f33e7 completed March 21, 2026, 2:53 p.m.
Created at: March 20, 2026, 1:38 p.m.