Triple

T1217211
Position Surface form Disambiguated ID Type / Status
Subject Serbia E26132 entity
Predicate highestPoint P210 FINISHED
Object Midžor
Midžor is a prominent mountain peak in the Balkan range on the Serbia–Bulgaria border, known for its scenic alpine landscapes and popularity among hikers.
 E156254 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: Midžor | Statement: [Serbia, highestPoint, Midžor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Midžor
Context triple: [Serbia, highestPoint, Midžor]
  • A. Mladenovac
    Mladenovac is a suburban municipality and town located in the southern part of the City of Belgrade, Serbia.
  • B. Obrenovac
    Obrenovac is a suburban municipality of Belgrade in Serbia, known for its industrial facilities and proximity to the Sava River.
  • C. Čukarica
    Čukarica is a municipality of Belgrade known for its mix of urban neighborhoods, industrial zones, and green areas along the Sava River.
  • D. Nikšić
    Nikšić is one of the largest cities in Montenegro, known as an important industrial, cultural, and educational center of the country.
  • E. Lazarevac
    Lazarevac is a suburban municipality of Belgrade in central Serbia, known for its coal mining industry and the Kolubara coal basin.
  • 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: Midžor
Triple: [Serbia, highestPoint, Midžor]
Generated description
Midžor is a prominent mountain peak in the Balkan range on the Serbia–Bulgaria border, known for its scenic alpine landscapes and popularity among hikers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Midžor
Target entity description: Midžor is a prominent mountain peak in the Balkan range on the Serbia–Bulgaria border, known for its scenic alpine landscapes and popularity among hikers.
  • A. Mladenovac
    Mladenovac is a suburban municipality and town located in the southern part of the City of Belgrade, Serbia.
  • B. Obrenovac
    Obrenovac is a suburban municipality of Belgrade in Serbia, known for its industrial facilities and proximity to the Sava River.
  • C. Čukarica
    Čukarica is a municipality of Belgrade known for its mix of urban neighborhoods, industrial zones, and green areas along the Sava River.
  • D. Nikšić
    Nikšić is one of the largest cities in Montenegro, known as an important industrial, cultural, and educational center of the country.
  • E. Lazarevac
    Lazarevac is a suburban municipality of Belgrade in central Serbia, known for its coal mining industry and the Kolubara coal basin.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be06d6308190a44c505e6b5e8d42 completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce5bdd248190a66551c814dcfac4 completed March 8, 2026, 1:18 a.m.
NEDg Description generation batch_69acceda83f08190b191c0c1432108b0 completed March 8, 2026, 1:20 a.m.
NED2 Entity disambiguation (via description) batch_69accfc65c008190affa13bee507bf6e completed March 8, 2026, 1:24 a.m.
Created at: March 1, 2026, 7:46 p.m.