Triple

T2792291
Position Surface form Disambiguated ID Type / Status
Subject GNU Core Utilities E61956 entity
Predicate contains P35 FINISHED
Object wc
wc is a GNU Core Utilities command-line program that counts lines, words, and bytes in text input.
 E299162 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: wc | Statement: [GNU Core Utilities, contains, wc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: wc
Context triple: [GNU Core Utilities, contains, wc]
  • A. W
    The W is a local New York City Subway service that runs on the BMT Broadway Line in Manhattan and Queens, typically operating on weekdays.
  • B. W
    W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
  • C. WR
    WR is the abbreviation for the German Council of Science and Humanities, a key advisory body that counsels the German federal and state governments on science, research, and higher education policy.
  • D. WR
    WR is the postcode area designation covering Worcester and surrounding parts of Worcestershire in England.
  • E. WR
    WR is the standard abbreviation for World Rugby, the international governing body for the sport of rugby union.
  • 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: wc
Triple: [GNU Core Utilities, contains, wc]
Generated description
wc is a GNU Core Utilities command-line program that counts lines, words, and bytes in text input.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: wc
Target entity description: wc is a GNU Core Utilities command-line program that counts lines, words, and bytes in text input.
  • A. W
    W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
  • B. W
    The W is a local New York City Subway service that runs on the BMT Broadway Line in Manhattan and Queens, typically operating on weekdays.
  • C. WR
    WR is the abbreviation for the German Council of Science and Humanities, a key advisory body that counsels the German federal and state governments on science, research, and higher education policy.
  • D. WR
    WR is the standard abbreviation for World Rugby, the international governing body for the sport of rugby union.
  • E. WR
    WR is the postcode area designation covering Worcester and surrounding parts of Worcestershire in England.
  • 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.