Triple

T6944206
Position Surface form Disambiguated ID Type / Status
Subject Taif Regional Airport E160753 entity
Predicate IATAcode P418 FINISHED
Object TIF
TIF is the IATA airport code for Taif Regional Airport, which serves the city of Taif in Saudi Arabia.
 E631614 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: TIF | Statement: [Taif Regional Airport, IATAcode, TIF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TIF
Context triple: [Taif Regional Airport, IATAcode, TIF]
  • A. TIF
    TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
  • B. TIF
    TIF is a major annual international trade fair held in Thessaloniki, Greece, showcasing products, services, and innovations from domestic and global exhibitors.
  • C. Tiff
    Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
  • D. TIFF
    TIFF is the non-profit cultural organization that runs the Toronto International Film Festival and related year-round film programs and events.
  • E. 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.
  • 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: TIF
Triple: [Taif Regional Airport, IATAcode, TIF]
Generated description
TIF is the IATA airport code for Taif Regional Airport, which serves the city of Taif in Saudi Arabia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TIF
Target entity description: TIF is the IATA airport code for Taif Regional Airport, which serves the city of Taif in Saudi Arabia.
  • A. TIF
    TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
  • B. TIF
    TIF is a major annual international trade fair held in Thessaloniki, Greece, showcasing products, services, and innovations from domestic and global exhibitors.
  • C. Tiff
    Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
  • D. TIFF
    TIFF is the non-profit cultural organization that runs the Toronto International Film Festival and related year-round film programs and events.
  • E. 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.
  • 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_69c6884f3db4819080ad65da69386206 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da88b79c8190a8f297dfc4972979 completed March 27, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75866a2408190b472fdad73a8799b completed March 28, 2026, 4:26 a.m.
NEDg Description generation batch_69c75a9485508190b65bb9447b0e3f69 completed March 28, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69c75b0ec4088190a492faea485dd7d1 completed March 28, 2026, 4:37 a.m.
Created at: March 27, 2026, 2:28 p.m.