Triple

T4277716
Position Surface form Disambiguated ID Type / Status
Subject TkAgg E97081 entity
Predicate supportsOutputFormat P23634 FINISHED
Object TIFF
TIFF (Tagged Image File Format) is a flexible, high-quality raster image format commonly used for storing detailed graphics and photographs, especially in professional imaging and printing workflows.
 E426685 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: TIFF | Statement: [TkAgg, supportsOutputFormat, TIFF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TIFF
Context triple: [TkAgg, supportsOutputFormat, TIFF]
  • A. TIFF
    TIFF is the non-profit cultural organization that runs the Toronto International Film Festival and related year-round film programs and events.
  • B. TIF
    TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
  • C. Tiff
    Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
  • D. MXF
    MXF is the IATA airport code for Maxwell Air Force Base, a United States Air Force installation located in Montgomery, Alabama.
  • E. Blackmagic RAW
    Blackmagic RAW is a high-quality, compressed raw video codec developed by Blackmagic Design that preserves extensive image data for flexible color grading and post-production workflows.
  • 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: TIFF
Triple: [TkAgg, supportsOutputFormat, TIFF]
Generated description
TIFF (Tagged Image File Format) is a flexible, high-quality raster image format commonly used for storing detailed graphics and photographs, especially in professional imaging and printing workflows.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TIFF
Target entity description: TIFF (Tagged Image File Format) is a flexible, high-quality raster image format commonly used for storing detailed graphics and photographs, especially in professional imaging and printing workflows.
  • A. TIFF
    TIFF is the non-profit cultural organization that runs the Toronto International Film Festival and related year-round film programs and events.
  • B. TIF
    TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
  • C. Tiff
    Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
  • D. MXF
    MXF is the IATA airport code for Maxwell Air Force Base, a United States Air Force installation located in Montgomery, Alabama.
  • E. Blackmagic RAW
    Blackmagic RAW is a high-quality, compressed raw video codec developed by Blackmagic Design that preserves extensive image data for flexible color grading and post-production workflows.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501ef1388190b0c968b069014a59 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b3b52c8190ae7c05448faf5558 completed March 14, 2026, 7:32 p.m.
NEDg Description generation batch_69b5b95083088190b0c993fa2fbc954c completed March 14, 2026, 7:38 p.m.
NED2 Entity disambiguation (via description) batch_69b5b9b8afcc8190822cfd560d064590 completed March 14, 2026, 7:40 p.m.
Created at: March 12, 2026, 11:07 p.m.