Triple

T17102393
Position Surface form Disambiguated ID Type / Status
Subject Tama area E415010 entity
Predicate hasPart P35 FINISHED
Object Hinode E193099 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: Hinode | Statement: [Tama area, hasPart, Hinode]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hinode
Context triple: [Tama area, hasPart, Hinode]
  • A. Hinode chosen
    Hinode is a small town in western Tokyo, Japan, known for its rural scenery and proximity to the Tama region’s mountains and forests.
  • B. Geotail
    Geotail is a Japanese–US scientific satellite mission launched in 1992 to study the structure and dynamics of Earth’s magnetotail and the solar wind’s interaction with the magnetosphere.
  • C. Akatsuki
    Akatsuki was an Imperial Japanese Navy destroyer of the Akatsuki class that served during World War II in the Pacific Theater.
  • D. Michibiki-1
    Michibiki-1 is a Japanese quasi-zenith navigation satellite that serves as part of the QZSS regional satellite positioning system to enhance GPS accuracy over Japan and the Asia-Oceania region.
  • E. Danuri
    Danuri is South Korea’s first lunar orbiter, designed to conduct scientific observations of the Moon and demonstrate the nation’s deep-space exploration capabilities.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc239a088190a776fe0f4361ffc7 completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139fdda488190a1ca5c7ca875e044 completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:35 a.m.