Triple

T12516292
Position Surface form Disambiguated ID Type / Status
Subject bzip2 E299198 entity
Predicate influenced P9 FINISHED
Object xz
xz is a modern lossless data compression format and toolset based on the LZMA algorithm, known for achieving high compression ratios and commonly used for software distribution and archival on Unix-like systems.
 E986435 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: xz | Statement: [bzip2, influenced, xz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: xz
Context triple: [bzip2, influenced, xz]
  • A. XUZ
    XUZ is the IATA airport code for Xuzhou Guanyin International Airport, a commercial airport serving the city of Xuzhou in Jiangsu Province, China.
  • B. ZW
    ZW is the ISO 3166-1 alpha-2 country code for Zimbabwe, a landlocked country in southern Africa.
  • C. ZA
    ZA is the ISO 3166-1 alpha-2 country code for South Africa.
  • D. OX
    OX is the postcode area covering Oxford and its surrounding region in Oxfordshire, England.
  • E. XZN
    XZN is the IATA station code assigned to the Avignon TGV high-speed railway station in southeastern France.
  • 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: xz
Triple: [bzip2, influenced, xz]
Generated description
xz is a modern lossless data compression format and toolset based on the LZMA algorithm, known for achieving high compression ratios and commonly used for software distribution and archival on Unix-like systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: xz
Target entity description: xz is a modern lossless data compression format and toolset based on the LZMA algorithm, known for achieving high compression ratios and commonly used for software distribution and archival on Unix-like systems.
  • A. XUZ
    XUZ is the IATA airport code for Xuzhou Guanyin International Airport, a commercial airport serving the city of Xuzhou in Jiangsu Province, China.
  • B. ZW
    ZW is the ISO 3166-1 alpha-2 country code for Zimbabwe, a landlocked country in southern Africa.
  • C. ZA
    ZA is the ISO 3166-1 alpha-2 country code for South Africa.
  • D. OX
    OX is the postcode area covering Oxford and its surrounding region in Oxfordshire, England.
  • E. XZN
    XZN is the IATA station code assigned to the Avignon TGV high-speed railway station in southeastern France.
  • 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.