Triple

T232767
Position Surface form Disambiguated ID Type / Status
Subject IEEE Transactions on Computers E4442 entity
Predicate hasAbbreviation P43 FINISHED
Object TC
TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
E29785 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: TC | Statement: [IEEE Transactions on Computers, hasAbbreviation, TC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TC
Context triple: [IEEE Transactions on Computers, hasAbbreviation, TC]
  • A. TCA
    TCA is the commonly used abbreviation for the Technical Cooperation Administration, a former U.S. government agency responsible for administering foreign aid and technical assistance programs.
  • B. TR
    TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
  • C. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • D. TEC
    TEC is the commonly used acronym for the Episcopal Church, a mainline Anglican Christian denomination based in the United States.
  • E. TW
    TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
  • 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: TC
Triple: [IEEE Transactions on Computers, hasAbbreviation, TC]
Generated description
TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TC
Target entity description: TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
  • A. TCA
    TCA is the commonly used abbreviation for the Technical Cooperation Administration, a former U.S. government agency responsible for administering foreign aid and technical assistance programs.
  • B. TR
    TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
  • C. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • D. TEC
    TEC is the commonly used acronym for the Episcopal Church, a mainline Anglican Christian denomination based in the United States.
  • E. TW
    TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
  • 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_69a257363ffc81909757bde7ab3404da completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25caf59948190bacac41a6ed84cb6 completed Feb. 28, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a362bd591c8190940e6b1cd81017ae completed Feb. 28, 2026, 9:48 p.m.
NEDg Description generation batch_69a3632a55ac8190b099ae109b0c578c completed Feb. 28, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_69a3639235808190aee80e49482486c2 completed Feb. 28, 2026, 9:52 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.