Triple

T2792293
Position Surface form Disambiguated ID Type / Status
Subject GNU Core Utilities E61956 entity
Predicate contains P35 FINISHED
Object paste
paste is a GNU Core Utilities command-line tool that merges lines of input files horizontally, typically separating fields with a delimiter such as a tab.
 E299163 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: paste | Statement: [GNU Core Utilities, contains, paste]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: paste
Context triple: [GNU Core Utilities, contains, paste]
  • A. PAP
    PAP is the legislative body of the African Union that aims to promote democracy, human rights, and integration across African states.
  • B. PAP
    PAP is the commonly used abbreviation for China’s paramilitary People’s Armed Police force responsible for internal security and law enforcement support.
  • C. Papel
    Papel is an indigenous language of Guinea-Bissau spoken primarily by the Papel people in the coastal regions around Bissau.
  • D. P
    P is the vehicle registration code used on license plates for the Czech city of Plzeň.
  • E. patchwork
    Patchwork is a web-based patch tracking system commonly used by open source projects, including Linux kernel development, to organize and review submitted code changes.
  • 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: paste
Triple: [GNU Core Utilities, contains, paste]
Generated description
paste is a GNU Core Utilities command-line tool that merges lines of input files horizontally, typically separating fields with a delimiter such as a tab.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: paste
Target entity description: paste is a GNU Core Utilities command-line tool that merges lines of input files horizontally, typically separating fields with a delimiter such as a tab.
  • A. PAP
    PAP is the legislative body of the African Union that aims to promote democracy, human rights, and integration across African states.
  • B. PAP
    PAP is the commonly used abbreviation for China’s paramilitary People’s Armed Police force responsible for internal security and law enforcement support.
  • C. Papel
    Papel is an indigenous language of Guinea-Bissau spoken primarily by the Papel people in the coastal regions around Bissau.
  • D. P
    P is the vehicle registration code used on license plates for the Czech city of Plzeň.
  • E. patchwork
    Patchwork is a web-based patch tracking system commonly used by open source projects, including Linux kernel development, to organize and review submitted code changes.
  • 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_69abddd107ac81908eb1a6946834eee3 completed March 7, 2026, 8:12 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.