Triple

T21583908
Position Surface form Disambiguated ID Type / Status
Subject M6 E532592 entity
Predicate satelliteService P19767 FINISHED
Object TNTSAT NE NERFINISHED

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: TNTSAT | Statement: [M6, satelliteService, TNTSAT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TNTSAT
Context triple: [M6, satelliteService, TNTSAT]
  • A. TNTSAT chosen
    TNTSAT is a French free-to-air satellite television platform that broadcasts the national digital terrestrial TV channels via satellite.
  • B. DPLL(T)
    DPLL(T) is a framework that extends the classic DPLL SAT-solving algorithm with theory solvers to efficiently decide satisfiability modulo background theories such as arithmetic, arrays, or bit-vectors.
  • C. 3sat
    3sat is a public, advertising-free cultural television channel jointly operated by German, Austrian, and Swiss broadcasters, focusing on highbrow arts, culture, and educational programming.
  • D. Boolean satisfiability problem
    The Boolean satisfiability problem (SAT) is the canonical NP-complete decision problem of determining whether there exists an assignment of truth values to variables that makes a given Boolean formula evaluate to true.
  • E. Boolector
    Boolector is an efficient SMT solver specialized in bit-vectors, arrays, and uninterpreted functions, widely used in formal verification and model checking.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c4618bec8190bcb0feb74568cbb1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb5f2cc0819095552de70eb2ad8d completed April 27, 2026, 4:51 a.m.
Created at: April 16, 2026, 6:31 p.m.