Triple

T10214082
Position Surface form Disambiguated ID Type / Status
Subject MetalKit E242398 entity
Predicate hasClass P9272 FINISHED
Object MTKMesh
MTKMesh is a MetalKit class that represents and manages mesh geometry for efficient rendering with Apple's Metal graphics framework.
 E849973 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: MTKMesh | Statement: [MetalKit, hasClass, MTKMesh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MTKMesh
Context triple: [MetalKit, hasClass, MTKMesh]
  • A. MTK
    MTK is the vehicle registration code for the Main-Taunus-Kreis district in the German state of Hesse.
  • B. MTL
    MTL is the standard three-letter abbreviation used for the National Hockey League team the Montreal Canadiens.
  • C. MTL
    MTL was the ISO 4217 currency code for the Maltese lira, the former national currency of Malta before adoption of the euro.
  • D. MTL
    MTL is a research and teaching facility at MIT focused on micro- and nanotechnology, including microelectronics, MEMS, and related advanced fabrication.
  • E. meshrep
    Meshrep is a traditional Uyghur community gathering that combines music, dance, oral storytelling, and social rituals to preserve and celebrate Uyghur cultural identity.
  • 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: MTKMesh
Triple: [MetalKit, hasClass, MTKMesh]
Generated description
MTKMesh is a MetalKit class that represents and manages mesh geometry for efficient rendering with Apple's Metal graphics framework.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MTKMesh
Target entity description: MTKMesh is a MetalKit class that represents and manages mesh geometry for efficient rendering with Apple's Metal graphics framework.
  • A. MTK
    MTK is the vehicle registration code for the Main-Taunus-Kreis district in the German state of Hesse.
  • B. MTL
    MTL was the ISO 4217 currency code for the Maltese lira, the former national currency of Malta before adoption of the euro.
  • C. MTL
    MTL is a research and teaching facility at MIT focused on micro- and nanotechnology, including microelectronics, MEMS, and related advanced fabrication.
  • D. MTL
    MTL is the standard three-letter abbreviation used for the National Hockey League team the Montreal Canadiens.
  • E. meshrep
    Meshrep is a traditional Uyghur community gathering that combines music, dance, oral storytelling, and social rituals to preserve and celebrate Uyghur cultural identity.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa24efc081909714d98943543283 completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d652ea80dc81908bc65ee2ec390467 completed April 8, 2026, 1:06 p.m.
NEDg Description generation batch_69d657818b008190a24170717cff53b9 completed April 8, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_69d65835a11c819083d069ab0f644d4c completed April 8, 2026, 1:29 p.m.
Created at: April 6, 2026, 11:04 a.m.