Triple

T953621
Position Surface form Disambiguated ID Type / Status
Subject Grok E20576 entity
Predicate hasModelVersion P11583 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: [Grok, hasModelVersion, Grok-1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grok-1
Context triple: [Grok, hasModelVersion, 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. 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.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasModelVersion
Context triple: [Grok, hasModelVersion, Grok-1]
  • A. hasVersionNumber chosen
    Indicates that an entity is associated with a specific version identifier or number.
  • B. hasStandardVersion
    Indicates that one entity serves as the official or canonical version of another entity.
  • C. hasVersionCount
    Indicates the total number of distinct versions associated with a given entity.
  • D. hasReleaseModel
    Indicates the type or strategy of release associated with an entity, such as how or under what model it is made available.
  • E. versioningModel
    Indicates that one entity serves as a versioning or revision-control model governing how versions of another entity are created, tracked, and managed.
  • F. None of above.

Provenance (4 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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3d8f2e0819097554a301f8aa70f completed March 1, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac119fd16c81908c43b6d3dc6d53b6 completed March 7, 2026, 11:53 a.m.
PD Predicate disambiguation batch_69a4b2a045308190ab94f3adab40db8d completed March 1, 2026, 9:41 p.m.
Created at: March 1, 2026, 7:40 p.m.