Triple

T3061213
Position Surface form Disambiguated ID Type / Status
Subject Visual Component Library E61999 entity
Predicate includes P1393 FINISHED
Object TImage
TImage is a VCL component in Delphi used to display and manipulate images within graphical user interfaces.
 E322644 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: TImage | Statement: [Visual Component Library, includes, TImage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TImage
Context triple: [Visual Component Library, includes, TImage]
  • A. Core Image
    Core Image is an Apple framework for high-performance image processing and analysis, offering GPU-accelerated filters and effects for macOS, iOS, and related platforms.
  • B. Images
    Images is a set of impressionistic piano pieces by Claude Debussy that evoke vivid, atmospheric soundscapes through innovative harmony and tone color.
  • C. TIF
    TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
  • D. Nu Image
    Nu Image is a film production company known for producing a wide range of genre movies, including action, thriller, and crime dramas.
  • E. Tiff
    Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
  • 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: TImage
Triple: [Visual Component Library, includes, TImage]
Generated description
TImage is a VCL component in Delphi used to display and manipulate images within graphical user interfaces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TImage
Target entity description: TImage is a VCL component in Delphi used to display and manipulate images within graphical user interfaces.
  • A. Core Image
    Core Image is an Apple framework for high-performance image processing and analysis, offering GPU-accelerated filters and effects for macOS, iOS, and related platforms.
  • B. Images
    Images is a set of impressionistic piano pieces by Claude Debussy that evoke vivid, atmospheric soundscapes through innovative harmony and tone color.
  • C. TIF
    TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
  • D. Nu Image
    Nu Image is a film production company known for producing a wide range of genre movies, including action, thriller, and crime dramas.
  • E. Tiff
    Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e9e1e248190b5ed5ebcdad1321e completed March 8, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef0e757481908eb1d9693474c49d completed March 11, 2026, 10:39 p.m.
NEDg Description generation batch_69b1efedc68481908c2fece012621f1f completed March 11, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69b1f07505c881909841f184af3e4319 completed March 11, 2026, 10:45 p.m.
Created at: March 8, 2026, 3:02 p.m.