Triple

T736072
Position Surface form Disambiguated ID Type / Status
Subject Titel E14934 entity
Predicate hasNearbyCity P350 FINISHED
Object Zrenjanin
Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
 E106219 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: Zrenjanin | Statement: [Titel, hasNearbyCity, Zrenjanin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zrenjanin
Context triple: [Titel, hasNearbyCity, Zrenjanin]
  • A. Novi Sad
    Novi Sad is Serbia’s second-largest city and the cultural and economic center of the northern Vojvodina region, known for its historic architecture and the EXIT music festival.
  • B. Niš
    Niš is one of the largest and oldest cities in Serbia, known as a key cultural, economic, and transportation hub in the southern part of the country.
  • C. Podgorica
    Podgorica is the capital and largest city of Montenegro, serving as its political, economic, and cultural center in the Balkans.
  • D. Zagreb
    Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
  • E. Sarajevo
    Sarajevo is the capital and largest city of Bosnia and Herzegovina, historically known as the site of Archduke Franz Ferdinand’s assassination that sparked World War I.
  • 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: Zrenjanin
Triple: [Titel, hasNearbyCity, Zrenjanin]
Generated description
Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zrenjanin
Target entity description: Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
  • A. Novi Sad
    Novi Sad is Serbia’s second-largest city and the cultural and economic center of the northern Vojvodina region, known for its historic architecture and the EXIT music festival.
  • B. Niš
    Niš is one of the largest and oldest cities in Serbia, known as a key cultural, economic, and transportation hub in the southern part of the country.
  • C. Podgorica
    Podgorica is the capital and largest city of Montenegro, serving as its political, economic, and cultural center in the Balkans.
  • D. Zagreb
    Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
  • E. Sarajevo
    Sarajevo is the capital and largest city of Bosnia and Herzegovina, historically known as the site of Archduke Franz Ferdinand’s assassination that sparked World War I.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5da30b88190afbd12ae6109cc1b completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c70997d081908a10e1aa4e936d32 completed March 4, 2026, 5:45 a.m.
NEDg Description generation batch_69a7c78161608190a9f5556639f9d97d completed March 4, 2026, 5:47 a.m.
NED2 Entity disambiguation (via description) batch_69a7c7e336c8819082bb3523c84fde4e completed March 4, 2026, 5:49 a.m.
Created at: March 1, 2026, 7:37 p.m.