Triple

T13489393
Position Surface form Disambiguated ID Type / Status
Subject Bundesstraße 96 E318592 entity
Predicate passesNear P416 FINISHED
Object Lauta
Lauta is a small town in the German state of Saxony, known for its location in the Lusatian region and its historical ties to lignite mining and industry.
 E1043692 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: Lauta | Statement: [Bundesstraße 96, passesNear, Lauta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lauta
Context triple: [Bundesstraße 96, passesNear, Lauta]
  • A. Laja
    Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
  • B. Laukaa
    Laukaa is a municipality in Central Finland known for its lakes, rural landscapes, and proximity to the city of Jyväskylä.
  • C. Vaala
    Vaala is a municipality in northern Finland known for its lakeside landscapes and location along the Oulujoki river.
  • D. Karosta
    Karosta is a historic former military port district in the Latvian city of Liepāja, known for its Tsarist-era fortifications, Soviet naval heritage, and distinctive coastal landscape.
  • E. Lisnaskea
    Lisnaskea is a small market town in County Fermanagh, Northern Ireland, known for serving as a local commercial and community hub for the surrounding rural area.
  • 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: Lauta
Triple: [Bundesstraße 96, passesNear, Lauta]
Generated description
Lauta is a small town in the German state of Saxony, known for its location in the Lusatian region and its historical ties to lignite mining and industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lauta
Target entity description: Lauta is a small town in the German state of Saxony, known for its location in the Lusatian region and its historical ties to lignite mining and industry.
  • A. Laja
    Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
  • B. Laukaa
    Laukaa is a municipality in Central Finland known for its lakes, rural landscapes, and proximity to the city of Jyväskylä.
  • C. Vaala
    Vaala is a municipality in northern Finland known for its lakeside landscapes and location along the Oulujoki river.
  • D. Karosta
    Karosta is a historic former military port district in the Latvian city of Liepāja, known for its Tsarist-era fortifications, Soviet naval heritage, and distinctive coastal landscape.
  • E. Lisnaskea
    Lisnaskea is a small market town in County Fermanagh, Northern Ireland, known for serving as a local commercial and community hub for the surrounding rural area.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf3cbe2081908c6792362c67c8f1 completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7463b758c8190abc0dd2a049d751e completed May 3, 2026, 12:57 p.m.
NEDg Description generation batch_69f74d048250819098baf78ff08c1633 completed May 3, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_69f750f7f11481908c60b49eef65b63f completed May 3, 2026, 1:43 p.m.
Created at: April 9, 2026, 9:43 p.m.