Triple

T13681613
Position Surface form Disambiguated ID Type / Status
Subject TEV E328016 entity
Predicate hasAbbreviation P43 FINISHED
Object TEV E328016 NE FINISHED

How this triple was built (2 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: TEV | Statement: [TEV, hasAbbreviation, TEV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TEV
Context triple: [TEV, hasAbbreviation, TEV]
  • A. TEV chosen
    TEV is a modern, easy-to-read English translation of the Bible, also known as the Today’s English Version or Good News Bible.
  • B. Vtek
    Vtek is a music producer known for working with the Nigerian singer Empress.
  • C. TEB
    TEB is the IATA airport code for Teterboro Airport, a major general aviation and corporate jet airport serving the New York City metropolitan area in New Jersey.
  • D. TEC
    TEC is the abbreviation for the Transatlantic Economic Council, a high-level forum for coordinating economic policy and regulatory cooperation between the United States and the European Union.
  • E. TEC
    TEC is a public transport company in Belgium that operates regional bus and other transit services, primarily in the Walloon region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66e75188190a9e82fdc5eb26513 completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944347a08190bc1386e78ddb3e71 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.