Triple

T12524327
Position Surface form Disambiguated ID Type / Status
Subject Lars Magnus Ericsson E299396 entity
Predicate placeOfBirth P1 FINISHED
Object Värmskog
Värmskog is a small locality in Värmland County, Sweden, known as the birthplace of telephone industry pioneer Lars Magnus Ericsson.
E986654 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: Värmskog | Statement: [Lars Magnus Ericsson, placeOfBirth, Värmskog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Värmskog
Context triple: [Lars Magnus Ericsson, placeOfBirth, Värmskog]
  • A. Fältskog
    Fältskog is a Swedish surname most famously borne by Agnetha Fältskog, the singer from the pop group ABBA.
  • B. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • C. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • D. Vänersborg
    Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
  • E. Bengtsfors
    Bengtsfors is a small town in western Sweden known for its lakeside setting, forests, and role as a local administrative and service center.
  • 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: Värmskog
Triple: [Lars Magnus Ericsson, placeOfBirth, Värmskog]
Generated description
Värmskog is a small locality in Värmland County, Sweden, known as the birthplace of telephone industry pioneer Lars Magnus Ericsson.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Värmskog
Target entity description: Värmskog is a small locality in Värmland County, Sweden, known as the birthplace of telephone industry pioneer Lars Magnus Ericsson.
  • A. Fältskog
    Fältskog is a Swedish surname most famously borne by Agnetha Fältskog, the singer from the pop group ABBA.
  • B. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • C. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • D. Vänersborg
    Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
  • E. Bengtsfors
    Bengtsfors is a small town in western Sweden known for its lakeside setting, forests, and role as a local administrative and service center.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545c2aa081908e8a5a94d30e23eb completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bc159c88190835fea5c0d9ee799 completed May 2, 2026, 7:08 p.m.
NEDg Description generation batch_69f64def9a6081908c3048f948829051 completed May 2, 2026, 7:18 p.m.
NED2 Entity disambiguation (via description) batch_69f64ea1719c8190b91ffaab60db25ad completed May 2, 2026, 7:21 p.m.
Created at: April 8, 2026, 9:57 p.m.