Triple

T9812671
Position Surface form Disambiguated ID Type / Status
Subject Hälsingland E238313 entity
Predicate hasCity P316 FINISHED
Object Söderhamn E825557 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: Söderhamn | Statement: [Hälsingland, hasCity, Söderhamn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Söderhamn
Context triple: [Hälsingland, hasCity, Söderhamn]
  • A. Söderhamn chosen
    Söderhamn is a coastal town in east-central Sweden known for its historical wooden architecture and role as the administrative and commercial center of the surrounding region.
  • B. Oskarshamn
    Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
  • C. Fredrikshamn
    Fredrikshamn (Hamina) is a coastal town in southeastern Finland that historically served as an important military and trading center.
  • D. Söderort
    Söderort is the southern suburban part of Stockholm, Sweden, consisting mainly of residential districts located south of the inner-city island of Södermalm.
  • E. Karlshamn
    Karlshamn is a coastal town in southern Sweden known for its harbor, archipelago, and role as a regional industrial and transport hub.
  • 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_69ca84defac48190abc1148804f184c1 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb222ba788190a9085272a3de7852 completed April 2, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23ceca020819080f310f84669551a completed April 5, 2026, 10:43 a.m.
Created at: March 30, 2026, 8:30 p.m.