Triple

T7228752
Position Surface form Disambiguated ID Type / Status
Subject Arafura-class offshore patrol vessel E154849 entity
Predicate manufacturer P490 FINISHED
Object Luerssen Australia E366092 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: Luerssen Australia | Statement: [Arafura-class offshore patrol vessel, manufacturer, Luerssen Australia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luerssen Australia
Context triple: [Arafura-class offshore patrol vessel, manufacturer, Luerssen Australia]
  • A. Lürssen chosen
    Lürssen is a renowned German shipyard specializing in the design and construction of luxury superyachts and naval vessels.
  • B. Hanse Sail
    Hanse Sail is a major annual maritime festival in Rostock, Germany, renowned for its gathering of traditional sailing ships and large windjammers from around the world.
  • C. Larsen
    Larsen is a surname of Scandinavian origin borne by numerous notable individuals across fields such as literature, music, and sports.
  • D. Ulstein
    Ulstein is a coastal municipality in western Norway known for its maritime industry and shipbuilding.
  • E. Jersey Marine
    Jersey Marine is a coastal village in South Wales known for its proximity to Swansea Bay and its historic tower landmark.
  • 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_69c68811dd1c8190ac460bb39e64e1f0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6e9e0ba248190a57a3b4fa8b858c7 completed March 27, 2026, 8:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc1cdfb88190934387e44531b732 completed March 28, 2026, 12:39 p.m.
Created at: March 27, 2026, 2:54 p.m.