Triple

T10628654
Position Surface form Disambiguated ID Type / Status
Subject Östersund Municipality E250390 entity
Predicate hasSettlement P1068 FINISHED
Object Häggenås
Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
E875718 NE FINISHED

How this triple was built (4 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: Häggenås | Statement: [Östersund Municipality, hasSettlement, Häggenås]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Häggenås
Context triple: [Östersund Municipality, hasSettlement, Häggenås]
  • A. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • B. Alingsås
    Alingsås is a Swedish town known for its historic wooden architecture, café culture, and annual Lights in Alingsås illumination festival.
  • C. Mönsterås
    Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
  • D. Fagersta
    Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
  • E. Mörbylånga
    Mörbylånga is a small coastal town on the Swedish island of Öland, known as a local center near the vast limestone plain of Stora Alvaret.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Häggenås
Triple: [Östersund Municipality, hasSettlement, Häggenås]
Generated description
Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Häggenås
Target entity description: Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
  • A. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • B. Alingsås
    Alingsås is a Swedish town known for its historic wooden architecture, café culture, and annual Lights in Alingsås illumination festival.
  • C. Mönsterås
    Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
  • D. Fagersta
    Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
  • E. Mörbylånga
    Mörbylånga is a small coastal town on the Swedish island of Öland, known as a local center near the vast limestone plain of Stora Alvaret.
  • F. None of above. chosen

Provenance (5 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df9228088190bdd57a95d8671618 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96babc290819096c0c914d038ba01 completed April 10, 2026, 9:29 p.m.
NEDg Description generation batch_69d96def8bfc81909d6a5addf724691b completed April 10, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69d96fedb18881908570593856f4aade completed April 10, 2026, 9:47 p.m.
Created at: April 8, 2026, 8:59 p.m.