Triple

T1048907
Position Surface form Disambiguated ID Type / Status
Subject Runasimi E22648 entity
Predicate nativeName P15 FINISHED
Object Runa Shimi E22648 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: Runa Shimi | Statement: [Runasimi, nativeName, Runa Shimi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Runa Shimi
Context triple: [Runasimi, nativeName, Runa Shimi]
  • A. Runashimi
    Runashimi is the Indigenous Kichwa (Quechua) language spoken primarily in the Andean regions of South America.
  • B. Geats
    The Geats were a North Germanic people from what is now southern Sweden, prominently featured in the Old English epic Beowulf as the hero’s own tribe.
  • C. Kintomo Mushakoji
    Kintomo Mushakoji was a Japanese diplomat who served as a key representative of Japan’s government in the 1930s, notably involved in its alignment with Axis powers.
  • D. Runasimi chosen
    Runasimi is the Indigenous Quechuan language family of the Andes, historically associated with the Inca Empire and still widely spoken across several South American countries.
  • E. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8b19a5c8190a532e025bd724088 completed March 1, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac53864a20819081fc59e7102a6e00 completed March 7, 2026, 4:34 p.m.
Created at: March 1, 2026, 7:42 p.m.