Triple

T923228
Position Surface form Disambiguated ID Type / Status
Subject Turner Broadcasting System E19927 entity
Predicate operates P24 FINISHED
Object TCM
TCM (Turner Classic Movies) is a television network known for broadcasting classic films, often uncut and commercial-free, from Hollywood’s golden age and beyond.
 E54382 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: TCM | Statement: [Turner Broadcasting System, operates, TCM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TCM
Context triple: [Turner Broadcasting System, operates, TCM]
  • A. TCM
    TCM is the IATA airport code for McChord Field at Joint Base Lewis–McChord in Washington State, USA.
  • B. TC
    TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
  • C. TC
    TC is the common abbreviation for the Trilateral Commission, a non-governmental policy discussion group that brings together leaders from North America, Europe, and Asia to address global issues.
  • D. TC
    TC is the Constitutional Court of Peru, the country’s highest body responsible for interpreting and safeguarding the constitution and constitutional rights.
  • E. TC
    TC is the two-letter ISO 3166-1 alpha-2 country code assigned to the Turks and Caicos Islands.
  • 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: TCM
Triple: [Turner Broadcasting System, operates, TCM]
Generated description
TCM (Turner Classic Movies) is a television network known for broadcasting classic films, often uncut and commercial-free, from Hollywood’s golden age and beyond.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TCM
Target entity description: TCM (Turner Classic Movies) is a television network known for broadcasting classic films, often uncut and commercial-free, from Hollywood’s golden age and beyond.
  • A. TCM chosen
    TCM is the IATA airport code for McChord Field at Joint Base Lewis–McChord in Washington State, USA.
  • B. TC
    TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
  • C. TC
    TC is the common abbreviation for the Trilateral Commission, a non-governmental policy discussion group that brings together leaders from North America, Europe, and Asia to address global issues.
  • D. TC
    TC is the two-letter ISO 3166-1 alpha-2 country code assigned to the Turks and Caicos Islands.
  • E. TC
    TC is the Constitutional Court of Peru, the country’s highest body responsible for interpreting and safeguarding the constitution and constitutional rights.
  • F. None of above.

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_69a493a099788190a696d9d8408cbaf4 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b314f6fc81908a3ccc2e741e3c2b completed March 1, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf6652d0819084d6216646bd4fc5 completed March 4, 2026, 6:21 a.m.
NEDg Description generation batch_69a7ebfdb6a08190bad4b12711719e80 completed March 4, 2026, 8:23 a.m.
NED2 Entity disambiguation (via description) batch_69a7ec6c239c8190a86ccf46232c74c4 completed March 4, 2026, 8:25 a.m.
Created at: March 1, 2026, 7:40 p.m.