Triple

T6195570
Position Surface form Disambiguated ID Type / Status
Subject Magura National Park E138500 entity
Predicate hasHighestPoint P210 FINISHED
Object Magura Wątkowska
Magura Wątkowska is a prominent peak in the Low Beskids mountain range of southeastern Poland, located within Magura National Park.
 E575433 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: Magura Wątkowska | Statement: [Magura National Park, hasHighestPoint, Magura Wątkowska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Magura Wątkowska
Context triple: [Magura National Park, hasHighestPoint, Magura Wątkowska]
  • A. Hala Gąsienicowa
    Hala Gąsienicowa is a picturesque alpine meadow in the Polish Tatra Mountains, popular as a hiking hub and starting point for routes to surrounding peaks and lakes.
  • B. Komorowska
    Komorowska is a Polish surname borne by various notable individuals in Poland.
  • C. Walewska
    Walewska is a Polish surname most famously associated with Maria Walewska, a noblewoman known as the mistress of Napoleon Bonaparte.
  • D. Michalina
    Michalina is a feminine given name of Slavic origin, commonly used in Polish-speaking countries.
  • E. Wasilewska
    Wasilewska is a Polish surname most notably associated with Wanda Wasilewska, a 20th-century Polish and Soviet writer and communist activist.
  • 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: Magura Wątkowska
Triple: [Magura National Park, hasHighestPoint, Magura Wątkowska]
Generated description
Magura Wątkowska is a prominent peak in the Low Beskids mountain range of southeastern Poland, located within Magura National Park.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Magura Wątkowska
Target entity description: Magura Wątkowska is a prominent peak in the Low Beskids mountain range of southeastern Poland, located within Magura National Park.
  • A. Hala Gąsienicowa
    Hala Gąsienicowa is a picturesque alpine meadow in the Polish Tatra Mountains, popular as a hiking hub and starting point for routes to surrounding peaks and lakes.
  • B. Komorowska
    Komorowska is a Polish surname borne by various notable individuals in Poland.
  • C. Walewska
    Walewska is a Polish surname most famously associated with Maria Walewska, a noblewoman known as the mistress of Napoleon Bonaparte.
  • D. Michalina
    Michalina is a feminine given name of Slavic origin, commonly used in Polish-speaking countries.
  • E. Wasilewska
    Wasilewska is a Polish surname most notably associated with Wanda Wasilewska, a 20th-century Polish and Soviet writer and communist activist.
  • 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_69c008ab9b3081908a11b2c744838435 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0624571508190bd273b4a051fbe41 completed March 22, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f234ffc8190a6e8166e2ac554a8 completed March 23, 2026, 4:49 p.m.
NEDg Description generation batch_69c1e32429f48190bc18f4d78f3c79e8 completed March 24, 2026, 1:04 a.m.
NED2 Entity disambiguation (via description) batch_69c1e4844f848190bf67d916851514bc completed March 24, 2026, 1:10 a.m.
Created at: March 22, 2026, 4:20 p.m.