Triple

T28067693
Position Surface form Disambiguated ID Type / Status
Subject Rover 800 E709298 entity
Predicate engineeringInfluence P61774 FINISHED
Object Japanese engineering LITERAL 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: Japanese engineering | Statement: [Rover 800, engineeringInfluence, Japanese engineering]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: engineeringInfluence
Context triple: [Rover 800, engineeringInfluence, Japanese engineering]
  • A. designInfluenceOn
    Indicates that one design, designer, or design-related factor has an effect on shaping, guiding, or altering another design or design outcome.
  • B. engineeringContribution
    Indicates a relationship where an entity contributes engineering work, expertise, or effort toward the design, development, or improvement of another entity.
  • C. engineeringEmphasis
    Indicates that something places a primary focus or specialization on engineering principles, methods, or activities.
  • D. influencedTechnology chosen
    Indicates that one entity has had a causal or shaping impact on the development, design, or use of a technological entity.
  • E. incorporatesInfluence
    Indicates that one entity integrates or absorbs the influence, ideas, or characteristics of another into itself.
  • F. None of above.

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_69ef9b6eb6d88190a3fea236eb0f7bed completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6401cee508190a0dd02cb60d72f3b completed May 2, 2026, 6:19 p.m.
PD Predicate disambiguation batch_69f63c6a8474819091b8c6fe98e3862d completed May 2, 2026, 6:03 p.m.
Created at: April 27, 2026, 8:44 p.m.