Triple

T7937917
Position Surface form Disambiguated ID Type / Status
Subject OpenStack E184327 entity
Predicate component P35 FINISHED
Object Nova
Nova is the OpenStack project that provides scalable, on-demand compute resources for running virtual machines and other instances in cloud environments.
E699713 NE FINISHED

How this triple was built (4 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: Nova | Statement: [OpenStack, component, Nova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nova
Context triple: [OpenStack, component, Nova]
  • A. Nova
    Nova is the name given to TransPennine Express’s modern fleet of intercity trains used across its key routes in the North of England and Scotland.
  • B. Nova
    Nova is a Spanish television channel that primarily targets female audiences with a mix of telenovelas, lifestyle programs, and entertainment content.
  • C. Nova Stella
    Nova Stella is the historic "new star" observed by Tycho Brahe in 1572, a supernova in the constellation Cassiopeia that helped transform early modern astronomy.
  • D. Nesta
    Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
  • E. Neo
    Neo is the protagonist of the science fiction film series "The Matrix," a hacker who becomes humanity's prophesied savior within a simulated reality.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nova
Triple: [OpenStack, component, Nova]
Generated description
Nova is the OpenStack project that provides scalable, on-demand compute resources for running virtual machines and other instances in cloud environments.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nova
Target entity description: Nova is the OpenStack project that provides scalable, on-demand compute resources for running virtual machines and other instances in cloud environments.
  • A. Nova
    Nova is the name given to TransPennine Express’s modern fleet of intercity trains used across its key routes in the North of England and Scotland.
  • B. Nova
    Nova is a Spanish television channel that primarily targets female audiences with a mix of telenovelas, lifestyle programs, and entertainment content.
  • C. Nova Stella
    Nova Stella is the historic "new star" observed by Tycho Brahe in 1572, a supernova in the constellation Cassiopeia that helped transform early modern astronomy.
  • D. Nesta
    Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
  • E. Neo
    Neo is the protagonist of the science fiction film series "The Matrix," a hacker who becomes humanity's prophesied savior within a simulated reality.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aef2394819086eea1f6ab117aed completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0a96ac819099ad30fb925eb329 completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb7634f4dc8190b5e537f24bccd651 completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbb67e77a48190b93c6ba61becfac4 completed March 31, 2026, 11:56 a.m.
Created at: March 30, 2026, 5:08 p.m.