Triple

T6107766
Position Surface form Disambiguated ID Type / Status
Subject RC Cola E136157 entity
Predicate hasSugarFreeVersion P52605 FINISHED
Object Diet RC E568818 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: Diet RC | Statement: [RC Cola, hasSugarFreeVersion, Diet RC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diet RC
Context triple: [RC Cola, hasSugarFreeVersion, Diet RC]
  • A. Diet RC chosen
    Diet RC is the sugar-free, low-calorie version of RC Cola designed as a diet soft drink alternative.
  • B. The Diet
    The Diet is Japan’s bicameral national legislature, consisting of the House of Representatives and the House of Councillors, responsible for making laws and selecting the Prime Minister.
  • C. Dietz
    Dietz is a historic town in the German state of Hesse that once served as the political center of the County of Nassau-Dietz.
  • D. EAT/DIE
    EAT/DIE is a conceptual artwork by American artist Robert Indiana that juxtaposes the words “EAT” and “DIE” to explore themes of consumption, mortality, and American culture.
  • E. Dizzasco
    Dizzasco is a small municipality in the Lombardy region of northern Italy, situated in the scenic Valle d’Intelvi near Lake Como.
  • 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_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b81fad081909b622cafc6d51249 completed March 22, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c13598c54c8190b3701de83005875c completed March 23, 2026, 12:44 p.m.
Created at: March 22, 2026, 4:13 p.m.