Triple

T2792802
Position Surface form Disambiguated ID Type / Status
Subject GNU Diffutils E61966 entity
Predicate includesUtility P16605 FINISHED
Object cmp
cmp is a GNU Diffutils command-line utility that compares two files byte by byte and reports the first difference it finds.
 E299205 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: cmp | Statement: [GNU Diffutils, includesUtility, cmp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: cmp
Context triple: [GNU Diffutils, includesUtility, cmp]
  • A. CMP
    CMP is the ICAO airline designator used to identify Copa Airlines in international aviation operations and communications.
  • B. COMP
    COMP is a scientific committee within the European Medicines Agency responsible for evaluating and advising on orphan medicinal products for rare diseases in the European Union.
  • C. COM
    COM (Component Object Model) is a Microsoft-developed software architecture that enables interprocess communication and reusable binary components across different programming languages and applications on Windows.
  • D. COR
    COR is the IATA airport code for Ingeniero Aeronáutico Ambrosio L.V. Taravella International Airport serving Córdoba, Argentina.
  • E. Cump
    Cump is the childhood nickname of William Tecumseh Sherman, the prominent Union general in the American Civil War.
  • 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: cmp
Triple: [GNU Diffutils, includesUtility, cmp]
Generated description
cmp is a GNU Diffutils command-line utility that compares two files byte by byte and reports the first difference it finds.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: cmp
Target entity description: cmp is a GNU Diffutils command-line utility that compares two files byte by byte and reports the first difference it finds.
  • A. CMP
    CMP is the ICAO airline designator used to identify Copa Airlines in international aviation operations and communications.
  • B. COMP
    COMP is a scientific committee within the European Medicines Agency responsible for evaluating and advising on orphan medicinal products for rare diseases in the European Union.
  • C. COM
    COM (Component Object Model) is a Microsoft-developed software architecture that enables interprocess communication and reusable binary components across different programming languages and applications on Windows.
  • D. COR
    COR is the IATA airport code for Ingeniero Aeronáutico Ambrosio L.V. Taravella International Airport serving Córdoba, Argentina.
  • E. Cump
    Cump is the childhood nickname of William Tecumseh Sherman, the prominent Union general in the American Civil War.
  • 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_69ab4b7f51d881908768300ebd2fbdae completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abe0895e5881909702e69aaee5c425 completed March 7, 2026, 8:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc65ebe788190859012e930918b05 completed March 10, 2026, 7:21 a.m.
NEDg Description generation batch_69afc6c6c620819098b76db174a6f98e completed March 10, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69afc72b2e3c8190aad78ac8924f07af completed March 10, 2026, 7:24 a.m.
Created at: March 6, 2026, 9:58 p.m.