Triple

T23250962
Position Surface form Disambiguated ID Type / Status
Subject TV total E581728 entity
Predicate hasSpinOff P7226 FINISHED
Object TV total Wok-WM 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: TV total Wok-WM | Statement: [TV total, hasSpinOff, TV total Wok-WM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TV total Wok-WM
Context triple: [TV total, hasSpinOff, TV total Wok-WM]
  • A. TV total chosen
    TV total is a popular German late-night comedy and talk show hosted by Stefan Raab that aired on the ProSieben television network.
  • B. We TV
    We TV is an American cable television network known for its reality programming focused on relationships, family life, and pop culture.
  • C. .tv
    .tv is the country-code top-level domain originally assigned to Tuvalu that has become popular worldwide for websites related to television and video content.
  • D. WTM
    WTM is the vehicle registration code used on license plates for vehicles registered in the Wittmund district of Lower Saxony, Germany.
  • E. TVH
    TVH is an Indian real estate and infrastructure development company known for sponsoring chess legend Viswanathan Anand.
  • 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_69e24606b17c81908aba1a4911c8a8ba completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f193f5aa9081909775fb7f7dc660b3 completed April 29, 2026, 5:15 a.m.
Created at: April 17, 2026, 4:10 p.m.