Triple

T4442678
Position Surface form Disambiguated ID Type / Status
Subject Hanami E96208 entity
Predicate hasComponent P35 FINISHED
Object Hanami::Controller E96208 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: Hanami::Controller | Statement: [Hanami, hasComponent, Hanami::Controller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanami::Controller
Context triple: [Hanami, hasComponent, Hanami::Controller]
  • A. Hanami chosen
    Hanami is a lightweight, modular Ruby web framework focused on simplicity, performance, and clear architecture for building web applications.
  • B. Shōhō
    Shōhō was a Japanese light aircraft carrier of the Imperial Japanese Navy during World War II, notable for being the first Japanese carrier sunk in the war during the Battle of the Coral Sea.
  • C. Hinokuma Hamanari
    Hinokuma Hamanari was a legendary figure in early Japanese history credited with helping establish the famous Buddhist temple Sensō-ji in Asakusa, Tokyo.
  • D. Haruku
    Haruku is an island in Indonesia’s Maluku (Moluccas) archipelago, known for its tropical environment and as part of the habitat range of the Moluccan megapode (Eulipoa wallacei).
  • E. Sakura
    Sakura is a Japanese high-speed Shinkansen train service that operates mainly on the Sanyo and Kyushu Shinkansen lines.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355aef21c819088f168a23f1933a6 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b61382d00481908b7c84f337b5cad7 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:32 p.m.