Triple

T12516252
Position Surface form Disambiguated ID Type / Status
Subject gzip E299197 entity
Predicate relatedFormat P26987 FINISHED
Object zlib
zlib is a widely used software library that provides lossless data compression using the DEFLATE algorithm.
E986434 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: zlib | Statement: [gzip, relatedFormat, zlib]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: zlib
Context triple: [gzip, relatedFormat, zlib]
  • A. gzip
    gzip is a widely used GNU file compression utility that reduces file size using the DEFLATE algorithm, commonly producing .gz archives on Unix-like systems.
  • B. bzip2
    bzip2 is a free and open-source data compression program known for its high compression ratios using the Burrows–Wheeler algorithm.
  • C. lzip
    lzip is a lossless data compression program and file format known for its high compression ratios, data integrity features, and use in software distribution archives.
  • D. LZIB
    LZIB is the ICAO airport code for M. R. Štefánik Airport, the main international airport serving Bratislava, Slovakia.
  • E. Zip2
    Zip2 was an early online city guide and business directory software company from the late 1990s that provided web-based publishing tools for newspapers.
  • 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: zlib
Triple: [gzip, relatedFormat, zlib]
Generated description
zlib is a widely used software library that provides lossless data compression using the DEFLATE algorithm.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: zlib
Target entity description: zlib is a widely used software library that provides lossless data compression using the DEFLATE algorithm.
  • A. gzip
    gzip is a widely used GNU file compression utility that reduces file size using the DEFLATE algorithm, commonly producing .gz archives on Unix-like systems.
  • B. bzip2
    bzip2 is a free and open-source data compression program known for its high compression ratios using the Burrows–Wheeler algorithm.
  • C. lzip
    lzip is a lossless data compression program and file format known for its high compression ratios, data integrity features, and use in software distribution archives.
  • D. LZIB
    LZIB is the ICAO airport code for M. R. Štefánik Airport, the main international airport serving Bratislava, Slovakia.
  • E. Zip2
    Zip2 was an early online city guide and business directory software company from the late 1990s that provided web-based publishing tools for newspapers.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541f80148190976d1d912fe155d0 completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bbd58b88190baeb99380babf64f completed May 2, 2026, 7:08 p.m.
NEDg Description generation batch_69f64ce257348190b01179773992d414 completed May 2, 2026, 7:13 p.m.
NED2 Entity disambiguation (via description) batch_69f64db823bc819098152a96db960b10 completed May 2, 2026, 7:17 p.m.
Created at: April 8, 2026, 9:57 p.m.