Triple

T16175211
Position Surface form Disambiguated ID Type / Status
Subject Imperial German Baltic Sea Division E392544 entity
Predicate locationOfLanding P117900 FINISHED
Object Hanko NE NERFINISHED

How this triple was built (3 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: Hanko | Statement: [Imperial German Baltic Sea Division, locationOfLanding, Hanko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanko
Context triple: [Imperial German Baltic Sea Division, locationOfLanding, Hanko]
  • A. Hanko chosen
    Hanko is a coastal town in southern Finland known for its beaches, maritime heritage, and status as the country’s southernmost city.
  • B. Hakodate
    Hakodate is a historic port city on Japan’s northern island of Hokkaido, known for its scenic night views from Mount Hakodate and its blend of Japanese and Western-influenced architecture.
  • C. Tsuruga
    Tsuruga is a coastal city in Fukui Prefecture, Japan, known as a key port and transportation hub on the Sea of Japan side of Honshu.
  • D. Shiohama
    Shiohama is a neighborhood located within Kōtō ward in Tokyo, Japan.
  • E. Kamaishi
    Kamaishi is a coastal city in northeastern Japan known for its historic iron and steel industry and as a venue for the 2019 Rugby World Cup.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: locationOfLanding
Context triple: [Imperial German Baltic Sea Division, locationOfLanding, Hanko]
  • A. landedNear
    Indicates that one entity has come to rest on a surface or location in close proximity to another specified entity or reference point.
  • B. firstStageLandingLocation
    Indicates the location where the first stage of a multi-stage launch vehicle lands or is intended to land.
  • C. landingPlace chosen
    Indicates the location or surface where something or someone comes down to rest after moving through the air or space.
  • D. typeOfLanding
    Indicates the specific kind or category of landing that occurs in a given event or situation.
  • E. lastFlightPlannedLandingSite
    Indicates the location where the most recent flight is scheduled to land.
  • F. None of above.

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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21ebab54c81908d82dd6a26c406c2 completed April 17, 2026, 11:51 a.m.
PD Predicate disambiguation batch_69e219d642708190ba31a90dce76a210 completed April 17, 2026, 11:30 a.m.
Created at: April 10, 2026, 5:02 a.m.