Triple

T4144322
Position Surface form Disambiguated ID Type / Status
Subject Central Lithuania E89346 entity
Predicate containsCity P294 FINISHED
Object Kazlų Rūda
Kazlų Rūda is a small town in central Lithuania known for its surrounding forests, timber industry, and railway connections.
 E415250 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: Kazlų Rūda | Statement: [Central Lithuania, containsCity, Kazlų Rūda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kazlų Rūda
Context triple: [Central Lithuania, containsCity, Kazlų Rūda]
  • A. Graudenz
    Graudenz is the German name for the historic city of Grudziądz, now in northern Poland, known for its medieval fortifications and strategic location on the Vistula River.
  • B. Muszyna
    Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
  • C. Wielka Krokiew
    Wielka Krokiew is a major ski jumping hill in Zakopane, Poland, known for hosting prominent international ski jumping competitions.
  • D. Tuchola Forest
    Tuchola Forest is one of Poland’s largest and most pristine forest complexes, known for its extensive pine woods, lakes, and protected natural landscapes.
  • E. Gietrzwałd
    Gietrzwałd is a village in northern Poland known as a Catholic pilgrimage site due to reported Marian apparitions in 1877.
  • 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: Kazlų Rūda
Triple: [Central Lithuania, containsCity, Kazlų Rūda]
Generated description
Kazlų Rūda is a small town in central Lithuania known for its surrounding forests, timber industry, and railway connections.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kazlų Rūda
Target entity description: Kazlų Rūda is a small town in central Lithuania known for its surrounding forests, timber industry, and railway connections.
  • A. Graudenz
    Graudenz is the German name for the historic city of Grudziądz, now in northern Poland, known for its medieval fortifications and strategic location on the Vistula River.
  • B. Muszyna
    Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
  • C. Wielka Krokiew
    Wielka Krokiew is a major ski jumping hill in Zakopane, Poland, known for hosting prominent international ski jumping competitions.
  • D. Tuchola Forest
    Tuchola Forest is one of Poland’s largest and most pristine forest complexes, known for its extensive pine woods, lakes, and protected natural landscapes.
  • E. Gietrzwałd
    Gietrzwałd is a village in northern Poland known as a Catholic pilgrimage site due to reported Marian apparitions in 1877.
  • 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_69b576d2f1788190847d38a384abbe67 completed March 14, 2026, 2:55 p.m.
NEDg Description generation batch_69b577ef7ed08190aca5f99d6abf1271 completed March 14, 2026, 2:59 p.m.
NED2 Entity disambiguation (via description) batch_69b578538e908190a2c7d9d80ec5ec99 completed March 14, 2026, 3:01 p.m.
Created at: March 9, 2026, 3:43 p.m.