Triple

T2792290
Position Surface form Disambiguated ID Type / Status
Subject GNU Core Utilities E61956 entity
Predicate contains P35 FINISHED
Object tr
tr is a GNU Core Utilities command-line program used to translate, squeeze, or delete characters from standard input and write the result to standard output.
 E299161 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: tr | Statement: [GNU Core Utilities, contains, tr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: tr
Context triple: [GNU Core Utilities, contains, tr]
  • A. TR
    TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
  • B. TRA
    TRA is the UK government body responsible for regulating the teaching profession, including overseeing teacher misconduct and maintaining professional standards.
  • C. tet
    tet is the ISO 639-1 language code for Tetum, an Austronesian language spoken primarily in East Timor.
  • D. TER
    TER is a network of regional express trains in France that provides local passenger rail services across various regions.
  • E. TH
    TH is the two-letter ISO 3166-1 alpha-2 country code assigned to Thailand for international standardization and identification.
  • 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: tr
Triple: [GNU Core Utilities, contains, tr]
Generated description
tr is a GNU Core Utilities command-line program used to translate, squeeze, or delete characters from standard input and write the result to standard output.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: tr
Target entity description: tr is a GNU Core Utilities command-line program used to translate, squeeze, or delete characters from standard input and write the result to standard output.
  • A. TR
    TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
  • B. TRA
    TRA is the UK government body responsible for regulating the teaching profession, including overseeing teacher misconduct and maintaining professional standards.
  • C. tet
    tet is the ISO 639-1 language code for Tetum, an Austronesian language spoken primarily in East Timor.
  • D. TER
    TER is a network of regional express trains in France that provides local passenger rail services across various regions.
  • E. TH
    TH is the two-letter ISO 3166-1 alpha-2 country code assigned to Thailand for international standardization and identification.
  • 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.