Triple

T13063651
Position Surface form Disambiguated ID Type / Status
Subject Norderstedt E329259 entity
Predicate hasSisterCity P919 FINISHED
Object Kohtla-Järve
Kohtla-Järve is an industrial city in northeastern Estonia known for its oil shale industry and diverse population.
 E1017487 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: Kohtla-Järve | Statement: [Norderstedt, hasSisterCity, Kohtla-Järve]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kohtla-Järve
Context triple: [Norderstedt, hasSisterCity, Kohtla-Järve]
  • A. Jõgeva
    Jõgeva is a small town in eastern Estonia known as a local administrative and cultural center and for recording some of the country’s lowest winter temperatures.
  • B. Tartu
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • C. Jõhvi
    Jõhvi is a town in northeastern Estonia that serves as the administrative center of Ida-Viru County.
  • D. Pärnu
    Pärnu is a coastal city in southwestern Estonia known as a popular summer resort and spa destination on the Baltic Sea.
  • E. Viljandi
    Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
  • 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: Kohtla-Järve
Triple: [Norderstedt, hasSisterCity, Kohtla-Järve]
Generated description
Kohtla-Järve is an industrial city in northeastern Estonia known for its oil shale industry and diverse population.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kohtla-Järve
Target entity description: Kohtla-Järve is an industrial city in northeastern Estonia known for its oil shale industry and diverse population.
  • A. Jõgeva
    Jõgeva is a small town in eastern Estonia known as a local administrative and cultural center and for recording some of the country’s lowest winter temperatures.
  • B. Tartu
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • C. Jõhvi
    Jõhvi is a town in northeastern Estonia that serves as the administrative center of Ida-Viru County.
  • D. Pärnu
    Pärnu is a coastal city in southwestern Estonia known as a popular summer resort and spa destination on the Baltic Sea.
  • E. Viljandi
    Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980e9bdfc81908eb90fb50597df64 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbe45c8c819080fbdf1d94376feb completed May 3, 2026, 4:15 a.m.
NEDg Description generation batch_69f6cd3d5090819091b65f544ad139fd completed May 3, 2026, 4:21 a.m.
NED2 Entity disambiguation (via description) batch_69f6cdc8d52c819083717a455d589646 completed May 3, 2026, 4:23 a.m.
Created at: April 9, 2026, 8:59 p.m.