Triple

T11565559
Position Surface form Disambiguated ID Type / Status
Subject Johan Skytte E274242 entity
Predicate workLocation P7 FINISHED
Object Dorpat E43129 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: Dorpat | Statement: [Johan Skytte, workLocation, Dorpat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dorpat
Context triple: [Johan Skytte, workLocation, Dorpat]
  • A. Viljandi
    Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
  • B. Tartu chosen
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • C. Vyborg
    Vyborg is a historic port city in northwestern Russia near the Finnish border, known for its medieval castle and long-contested status between Sweden, Finland, and Russia.
  • D. Jakobstad
    Jakobstad is a coastal town and municipality in western Finland known for its bilingual (Finnish and Swedish) heritage and maritime history.
  • E. Porvoo
    Porvoo is a historic coastal city in southern Finland known for its well-preserved wooden Old Town and medieval cathedral.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd321f88190a57ecaf079fbbc3f completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e8b1a67481909a05105728acc358 completed April 21, 2026, 3:02 a.m.
Created at: April 8, 2026, 9:37 p.m.