Triple

T16624397
Position Surface form Disambiguated ID Type / Status
Subject Jak II E403909 entity
Predicate gameEngine P26587 FINISHED
Object Kinetica
Kinetica is a proprietary game engine developed by Sony Computer Entertainment, known for powering several early PlayStation 2 titles.
E1224646 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: Kinetica | Statement: [Jak II, gameEngine, Kinetica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kinetica
Context triple: [Jak II, gameEngine, Kinetica]
  • A. Vertica
    Vertica is a high-performance, column-oriented analytical database system designed for large-scale data warehousing and real-time analytics.
  • B. Actian
    Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
  • C. Greenplum
    Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
  • D. Ebixa
    Ebixa is a brand-name medication containing memantine, used primarily to treat moderate to severe Alzheimer's disease.
  • E. SciDB
    SciDB is an open-source array database management system designed for large-scale scientific and multidimensional data analytics.
  • 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: Kinetica
Triple: [Jak II, gameEngine, Kinetica]
Generated description
Kinetica is a proprietary game engine developed by Sony Computer Entertainment, known for powering several early PlayStation 2 titles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kinetica
Target entity description: Kinetica is a proprietary game engine developed by Sony Computer Entertainment, known for powering several early PlayStation 2 titles.
  • A. Vertica
    Vertica is a high-performance, column-oriented analytical database system designed for large-scale data warehousing and real-time analytics.
  • B. Actian
    Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
  • C. Greenplum
    Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
  • D. Ebixa
    Ebixa is a brand-name medication containing memantine, used primarily to treat moderate to severe Alzheimer's disease.
  • E. SciDB
    SciDB is an open-source array database management system designed for large-scale scientific and multidimensional data analytics.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37550ee308190931fd50aeebe1e7e completed April 18, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007db866e48190886aec7658835543 completed May 10, 2026, 12:44 p.m.
NEDg Description generation batch_6a007ee625c48190a7a97f34d5788808 completed May 10, 2026, 12:49 p.m.
NED2 Entity disambiguation (via description) batch_6a007f75e7e48190ac5cf912cca60d9c completed May 10, 2026, 12:52 p.m.
Created at: April 10, 2026, 5:17 a.m.