Triple

T2448383
Position Surface form Disambiguated ID Type / Status
Subject Slovak Ore Mountains E53644 entity
Predicate highestPoint P210 FINISHED
Object Stolica
Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
 E268884 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: Stolica | Statement: [Slovak Ore Mountains, highestPoint, Stolica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stolica
Context triple: [Slovak Ore Mountains, highestPoint, Stolica]
  • A. Karlov
    Karlov is a historic university campus complex in Prague that houses several faculties of Charles University, particularly in the medical and natural sciences.
  • B. Lefortovo
    Lefortovo is a Moscow Metro station on the Big Circle Line serving the historic Lefortovo district of Russia’s capital.
  • C. Gollob
    Gollob is a surname most notably associated with Gordon Gollob, a distinguished German Luftwaffe fighter ace of World War II.
  • D. Perovo
    Perovo is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Perovo District of eastern Moscow.
  • E. Karlovasi
    Karlovasi is a coastal town on the Greek island of Samos, known for its neoclassical architecture, port, and role as a local commercial and educational center.
  • 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: Stolica
Triple: [Slovak Ore Mountains, highestPoint, Stolica]
Generated description
Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stolica
Target entity description: Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
  • A. Karlov
    Karlov is a historic university campus complex in Prague that houses several faculties of Charles University, particularly in the medical and natural sciences.
  • B. Lefortovo
    Lefortovo is a Moscow Metro station on the Big Circle Line serving the historic Lefortovo district of Russia’s capital.
  • C. Gollob
    Gollob is a surname most notably associated with Gordon Gollob, a distinguished German Luftwaffe fighter ace of World War II.
  • D. Perovo
    Perovo is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Perovo District of eastern Moscow.
  • E. Karlovasi
    Karlovasi is a coastal town on the Greek island of Samos, known for its neoclassical architecture, port, and role as a local commercial and educational center.
  • 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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0dc7ed88190920afd4817c621c9 completed March 7, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0c0069c8190bfb9e71aea4774d3 completed March 9, 2026, 4:09 p.m.
NEDg Description generation batch_69aef53740508190893b14bb1b411a30 completed March 9, 2026, 4:28 p.m.
NED2 Entity disambiguation (via description) batch_69aef9594024819088e7afc0e64429ff completed March 9, 2026, 4:46 p.m.
Created at: March 6, 2026, 9:43 p.m.