Triple

T16404822
Position Surface form Disambiguated ID Type / Status
Subject Port of Beppu E398398 entity
Predicate serves P98 FINISHED
Object city of Beppu E1211727 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: city of Beppu | Statement: [Port of Beppu, serves, city of Beppu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Beppu
Context triple: [Port of Beppu, serves, city of Beppu]
  • A. Beppu City chosen
    Beppu City is a famous hot spring resort city in Ōita Prefecture, Japan, renowned for its numerous onsen and unique geothermal attractions.
  • B. Ibusuki
    Ibusuki is a coastal city in Kagoshima Prefecture, Japan, best known for its natural hot springs and unique sand bath spas.
  • C. Atami
    Atami is a coastal hot spring resort city in Shizuoka Prefecture, Japan, known for its onsen, beaches, and proximity to Tokyo.
  • D. Nobeoka City
    Nobeoka City is a coastal city in southeastern Kyushu, Japan, known for its chemical and electronics industries and scenic natural surroundings.
  • E. Miyakonojo City
    Miyakonojo City is a regional city in southern Japan known for its agriculture, livestock production, and location within Miyazaki Prefecture on the island of Kyushu.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e327d1f16481909adb19dab86dcc72 completed April 18, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00457baed48190b559af7c0ac2711d completed May 10, 2026, 8:44 a.m.
Created at: April 10, 2026, 5:09 a.m.