Triple

T10738487
Position Surface form Disambiguated ID Type / Status
Subject Heike Makatsch E253256 entity
Predicate givenName P17 FINISHED
Object Heike E253255 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: Heike | Statement: [Heike Makatsch, givenName, Heike]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heike
Context triple: [Heike Makatsch, givenName, Heike]
  • A. Heike chosen
    Heike is a feminine given name of German origin, commonly used in German-speaking countries.
  • B. Saigō-no-Tsubone
    Saigō-no-Tsubone was a prominent Japanese noblewoman and concubine of Tokugawa Ieyasu who became an influential figure in the early Edo period through her role in the Tokugawa shogunate.
  • C. Katsuragi
    Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
  • D. Katsuragi
    Katsuragi was a late-war Imperial Japanese Navy aircraft carrier that served in the Pacific Theater during World War II.
  • E. Obihiro
    Obihiro is a mid-sized city in eastern Hokkaido, Japan, known for its agricultural production, horse racing, and cold, snowy winters.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710424d8c81908ee9b59d622f2af5 completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69de22ed6edc8190beb76bd2971c7cec completed April 14, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:14 p.m.