Triple

T4144320
Position Surface form Disambiguated ID Type / Status
Subject Central Lithuania E89346 entity
Predicate containsCity P294 FINISHED
Object Marijampolė
Marijampolė is a city in southern Lithuania that serves as an important regional center for administration, culture, and industry.
 E443213 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: Marijampolė | Statement: [Central Lithuania, containsCity, Marijampolė]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marijampolė
Context triple: [Central Lithuania, containsCity, Marijampolė]
  • A. Trakai
    Trakai is a historic Lithuanian town famed for its medieval island castle and former status as a political center of the Grand Duchy of Lithuania.
  • B. Alytus
    Alytus is a city in southern Lithuania known as a regional cultural and economic center on the banks of the Nemunas River.
  • C. Vilkaviškis
    Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
  • D. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • E. Kovno
    Kovno is the historical name for Kaunas, a major city in Lithuania that was once part of the Russian Empire and had a significant Jewish community.
  • 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: Marijampolė
Triple: [Central Lithuania, containsCity, Marijampolė]
Generated description
Marijampolė is a city in southern Lithuania that serves as an important regional center for administration, culture, and industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marijampolė
Target entity description: Marijampolė is a city in southern Lithuania that serves as an important regional center for administration, culture, and industry.
  • A. Trakai
    Trakai is a historic Lithuanian town famed for its medieval island castle and former status as a political center of the Grand Duchy of Lithuania.
  • B. Alytus
    Alytus is a city in southern Lithuania known as a regional cultural and economic center on the banks of the Nemunas River.
  • C. Vilkaviškis
    Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
  • D. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • E. Kovno
    Kovno is the historical name for Kaunas, a major city in Lithuania that was once part of the Russian Empire and had a significant Jewish community.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af025d2984819095f299327cc399d5 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b63725b9348190af56a6b7477de03f completed March 15, 2026, 4:35 a.m.
NEDg Description generation batch_69b637b12bcc8190b040927ba9a5b24f completed March 15, 2026, 4:38 a.m.
NED2 Entity disambiguation (via description) batch_69b6383aecb081908c0dc402b8f4add5 completed March 15, 2026, 4:40 a.m.
Created at: March 9, 2026, 3:43 p.m.