Triple

T17257170
Position Surface form Disambiguated ID Type / Status
Subject Tauragė County E418911 entity
Predicate hasIndustrialCentre P60143 FINISHED
Object Šilalė
Šilalė is a small town in western Lithuania known as a local administrative and economic center within Tauragė County.
 E1259424 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: Šilalė | Statement: [Tauragė County, hasIndustrialCentre, Šilalė]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Šilalė
Context triple: [Tauragė County, hasIndustrialCentre, Šilalė]
  • A. Plungė
    Plungė is a town in northwestern Lithuania that serves as an important cultural and economic center of the Samogitia region.
  • B. Šešupė
    Šešupė is a river in northeastern Europe that flows through Lithuania, Poland, and Russia before joining the Neman River.
  • C. Šilutė
    Šilutė is a town in western Lithuania known for its location near the Nemunas River delta and its historical ties to the former East Prussian region.
  • D. Kuršumlija
    Kuršumlija is a small town and municipality in southern Serbia, known for its nearby monasteries and location at the confluence of the Toplica and Kosanica rivers.
  • E. Pielavesi
    Pielavesi is a rural municipality in Northern Savonia, Finland, best known as the birthplace of long-serving Finnish president Urho Kekkonen.
  • 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: Šilalė
Triple: [Tauragė County, hasIndustrialCentre, Šilalė]
Generated description
Šilalė is a small town in western Lithuania known as a local administrative and economic center within Tauragė County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Šilalė
Target entity description: Šilalė is a small town in western Lithuania known as a local administrative and economic center within Tauragė County.
  • A. Plungė
    Plungė is a town in northwestern Lithuania that serves as an important cultural and economic center of the Samogitia region.
  • B. Šešupė
    Šešupė is a river in northeastern Europe that flows through Lithuania, Poland, and Russia before joining the Neman River.
  • C. Šilutė
    Šilutė is a town in western Lithuania known for its location near the Nemunas River delta and its historical ties to the former East Prussian region.
  • D. Kuršumlija
    Kuršumlija is a small town and municipality in southern Serbia, known for its nearby monasteries and location at the confluence of the Toplica and Kosanica rivers.
  • E. Pielavesi
    Pielavesi is a rural municipality in Northern Savonia, Finland, best known as the birthplace of long-serving Finnish president Urho Kekkonen.
  • 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e6dde4881908e7fc01fd5364616 completed April 19, 2026, 1:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170ff6818819090077dc4a7b774ae completed May 11, 2026, 6:02 a.m.
NEDg Description generation batch_6a017521c90c819099cea67e4084aa67 completed May 11, 2026, 6:20 a.m.
NED2 Entity disambiguation (via description) batch_6a01760409ac8190ac7714e31e686d9a completed May 11, 2026, 6:24 a.m.
Created at: April 10, 2026, 5:39 a.m.