Triple

T146413
Position Surface form Disambiguated ID Type / Status
Subject xAI E3339 entity
Predicate hasLanguageModel P7183 FINISHED
Object Grok-1 E20576 NE FINISHED

How this triple was built (3 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: Grok-1 | Statement: [xAI, hasLanguageModel, Grok-1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grok-1
Context triple: [xAI, hasLanguageModel, Grok-1]
  • A. Grok chosen
    Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
  • B. 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.
  • C. GPT-2
    GPT-2 is a large transformer-based language model known for generating coherent, human-like text and sparking widespread discussion about the implications of advanced AI text generation.
  • D. GPT-4
    GPT-4 is a large multimodal language model known for its advanced reasoning, comprehension, and generation capabilities across text and images.
  • E. GPT-3.5
    GPT-3.5 is a large language model that generates human-like text and powers conversational AI applications such as advanced chatbots and coding assistants.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLanguageModel
Context triple: [xAI, hasLanguageModel, Grok-1]
  • A. hasSignificantLanguage
    Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
  • B. hasProtoLanguage
    Indicates that a language or language family originates from, or is derived from, a specified proto-language.
  • C. recognizedLanguage
    Indicates that an entity has identified, detected, or acknowledged a particular language as being used or present.
  • D. hasLanguageGroup
    Indicates that an entity belongs to, is associated with, or is categorized under a particular language group.
  • E. isLanguageOf
    Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
  • F. None of above. chosen

Provenance (5 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_69a252868de4819080e21c9938bfe8b6 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a258808ff08190a06b6206f635612b completed Feb. 28, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2e0f4eef081908a20426715283e68 completed Feb. 28, 2026, 12:35 p.m.
PD Predicate disambiguation batch_69a256580c2c8190beecca60ca8595f3 completed Feb. 28, 2026, 2:43 a.m.
PDg Predicate description generation batch_69a2587e598c81909e1082b813971f48 completed Feb. 28, 2026, 2:52 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.