Triple

T12983961
Position Surface form Disambiguated ID Type / Status
Subject Lake Vättern E321719 entity
Predicate adjacentCity P5707 FINISHED
Object Hjo
Hjo is a small historic town in southern Sweden known for its well-preserved wooden architecture and lakeside location.
 E1012566 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: Hjo | Statement: [Lake Vättern, adjacentCity, Hjo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hjo
Context triple: [Lake Vättern, adjacentCity, Hjo]
  • A. Høvelte
    Høvelte is a locality in Denmark known primarily for hosting a major Danish Army military barracks and training area.
  • B. Hisingen
    Hisingen is a large island and district in Gothenburg, Sweden, known for its industrial areas, shipyards, and rapidly developing residential and tech hubs.
  • C. Bruhagen
    Bruhagen is a village and administrative center located on the island of Averøya in Møre og Romsdal county, Norway.
  • D. Haukio
    Haukio is a Finnish surname most notably borne by Jenni Haukio, a poet and the spouse of Finland’s president.
  • E. Harestua
    Harestua is a village in Viken county, Norway, known for its residential community and proximity to the Harestua Solar Observatory.
  • 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: Hjo
Triple: [Lake Vättern, adjacentCity, Hjo]
Generated description
Hjo is a small historic town in southern Sweden known for its well-preserved wooden architecture and lakeside location.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hjo
Target entity description: Hjo is a small historic town in southern Sweden known for its well-preserved wooden architecture and lakeside location.
  • A. Høvelte
    Høvelte is a locality in Denmark known primarily for hosting a major Danish Army military barracks and training area.
  • B. Hisingen
    Hisingen is a large island and district in Gothenburg, Sweden, known for its industrial areas, shipyards, and rapidly developing residential and tech hubs.
  • C. Bruhagen
    Bruhagen is a village and administrative center located on the island of Averøya in Møre og Romsdal county, Norway.
  • D. Haukio
    Haukio is a Finnish surname most notably borne by Jenni Haukio, a poet and the spouse of Finland’s president.
  • E. Harestua
    Harestua is a village in Viken county, Norway, known for its residential community and proximity to the Harestua Solar Observatory.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e5e3f208190abd2d4b4d5114834 completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8f4320881909d66eaa48f888fab completed May 3, 2026, 2:54 a.m.
NEDg Description generation batch_69f6b9dc31ec819093c89ff0a1ccbfa1 completed May 3, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69f6baacd7548190af5514923a0dee26 completed May 3, 2026, 3:02 a.m.
Created at: April 9, 2026, 8:39 p.m.