Triple

T13209644
Position Surface form Disambiguated ID Type / Status
Subject Vasa Museum E314453 entity
Predicate exhibits P4908 FINISHED
Object Vasa (warship) E311349 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: Vasa (warship) | Statement: [Vasa Museum, exhibits, Vasa (warship)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vasa (warship)
Context triple: [Vasa Museum, exhibits, Vasa (warship)]
  • A. Vasa (warship) chosen
    Vasa (warship) is a 17th-century Swedish warship that famously sank on its maiden voyage in 1628 and was later salvaged to become one of the world’s best-preserved historic ships.
  • B. Vasa
    Vasa was a prominent royal dynasty in Sweden and Poland-Lithuania that produced several influential monarchs during the 16th and 17th centuries.
  • C. Pommern museum ship
    The Pommern museum ship is a preserved early 20th-century four-masted steel barque, now serving as a maritime museum in Mariehamn, Åland.
  • D. Gangut
    Gangut was a Russian ship of the line that served in the Imperial Russian Navy and took part in major 19th-century naval engagements.
  • E. Gunnor
    Gunnor was a powerful Norman noblewoman and duchess, influential in the politics of Normandy as the wife of Duke Richard I and ancestress of the ducal and English royal 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9e072c8190b66e2c2430628ed0 completed April 10, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f611b11c8190b9f89313eb2b5fab completed May 3, 2026, 7:15 a.m.
Created at: April 9, 2026, 9:17 p.m.