Triple

T6915404
Position Surface form Disambiguated ID Type / Status
Subject Kamnik–Savinja Alps E160037 entity
Predicate hasPeak P8205 FINISHED
Object Skuta
Skuta is a prominent mountain peak in Slovenia known for its rugged alpine terrain and scenic hiking and climbing routes.
 E627299 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: Skuta | Statement: [Kamnik–Savinja Alps, hasPeak, Skuta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Skuta
Context triple: [Kamnik–Savinja Alps, hasPeak, Skuta]
  • A. Nogliki
    Nogliki is a small town and administrative center in northern Sakhalin, Russia, known primarily for its role in supporting the island’s oil and gas industry.
  • B. Šolta
    Šolta is a small Croatian island in the Adriatic Sea, known for its tranquil villages, olive groves, and clear bays, located just off the coast from the city of Split.
  • C. Susak
    Susak is a small, sandy Croatian island in the Adriatic Sea known for its unique geology, distinct local dialect, and traditional folk costumes.
  • D. Дьокуускай
    Дьокуускай is the Sakha (Yakut) name for Yakutsk, the capital city of Russia’s Sakha Republic in northeastern Siberia.
  • E. Kopaska
    Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
  • 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: Skuta
Triple: [Kamnik–Savinja Alps, hasPeak, Skuta]
Generated description
Skuta is a prominent mountain peak in Slovenia known for its rugged alpine terrain and scenic hiking and climbing routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Skuta
Target entity description: Skuta is a prominent mountain peak in Slovenia known for its rugged alpine terrain and scenic hiking and climbing routes.
  • A. Nogliki
    Nogliki is a small town and administrative center in northern Sakhalin, Russia, known primarily for its role in supporting the island’s oil and gas industry.
  • B. Šolta
    Šolta is a small Croatian island in the Adriatic Sea, known for its tranquil villages, olive groves, and clear bays, located just off the coast from the city of Split.
  • C. Susak
    Susak is a small, sandy Croatian island in the Adriatic Sea known for its unique geology, distinct local dialect, and traditional folk costumes.
  • D. Дьокуускай
    Дьокуускай is the Sakha (Yakut) name for Yakutsk, the capital city of Russia’s Sakha Republic in northeastern Siberia.
  • E. Kopaska
    Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
  • 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_69c6883ab1008190a07129ff06f625d9 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9dec058819094d1913a1e5218c0 completed March 27, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7491589c08190982a84f2b61b497b completed March 28, 2026, 3:20 a.m.
NEDg Description generation batch_69c749e5a4188190829f534a12730c76 completed March 28, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_69c74aaccf6c819084556ede9ffc0f19 completed March 28, 2026, 3:27 a.m.
Created at: March 27, 2026, 2:26 p.m.