Triple

T4821345
Position Surface form Disambiguated ID Type / Status
Subject Västergötland E107715 entity
Predicate containsTown P847 FINISHED
Object Lödöse
Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
 E475434 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: Lödöse | Statement: [Västergötland, containsTown, Lödöse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lödöse
Context triple: [Västergötland, containsTown, Lödöse]
  • A. Liausson
    Liausson is a small commune in southern France’s Hérault department, known for its scenic setting on the shores of the artificial Lac du Salagou.
  • B. Lönnbohm
    Lönnbohm is the original family name of the renowned Finnish poet and journalist Eino Leino.
  • C. Lögberg
    Lögberg is the historic Law Rock at Þingvellir in Iceland, where the Althing, one of the world’s oldest parliaments, traditionally convened and laws were proclaimed.
  • D. Lesja
    Lesja is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, agriculture, and outdoor recreation opportunities.
  • E. Odda
    Odda is a town in western Norway known for its dramatic fjord landscape, industrial heritage, and proximity to popular hiking destinations like Trolltunga.
  • 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: Lödöse
Triple: [Västergötland, containsTown, Lödöse]
Generated description
Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lödöse
Target entity description: Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
  • A. Liausson
    Liausson is a small commune in southern France’s Hérault department, known for its scenic setting on the shores of the artificial Lac du Salagou.
  • B. Lönnbohm
    Lönnbohm is the original family name of the renowned Finnish poet and journalist Eino Leino.
  • C. Lögberg
    Lögberg is the historic Law Rock at Þingvellir in Iceland, where the Althing, one of the world’s oldest parliaments, traditionally convened and laws were proclaimed.
  • D. Lesja
    Lesja is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, agriculture, and outdoor recreation opportunities.
  • E. Odda
    Odda is a town in western Norway known for its dramatic fjord landscape, industrial heritage, and proximity to popular hiking destinations like Trolltunga.
  • 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_69bd43f9efa081908314cb3e94fa1695 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6c99b46c8190b6fbcf9f98b9e993 completed March 20, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5cb34004819086809b4a7071f4a5 completed March 21, 2026, 8:54 a.m.
NEDg Description generation batch_69be607df6648190be22b5bc0d6531b4 completed March 21, 2026, 9:10 a.m.
NED2 Entity disambiguation (via description) batch_69be611da7c08190b644cfbcb30741fc completed March 21, 2026, 9:13 a.m.
Created at: March 20, 2026, 1:24 p.m.