Triple

T19014010
Position Surface form Disambiguated ID Type / Status
Subject Jadranka Kosor E465299 entity
Predicate familyName P18 FINISHED
Object Kosor
Kosor is a Croatian surname most notably borne by Jadranka Kosor, a former Prime Minister of Croatia.
 E1355312 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: Kosor | Statement: [Jadranka Kosor, familyName, Kosor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kosor
Context triple: [Jadranka Kosor, familyName, Kosor]
  • A. Zala
    Zala is a river in western Hungary that flows into Lake Balaton and lends its name to the surrounding Zala region.
  • B. Moslavina
    Moslavina is a historical and geographical region in central Croatia known for its rural landscapes, vineyards, and small towns.
  • C. Vreoci
    Vreoci is a suburban settlement in the Lazarevac municipality of Belgrade, Serbia, known for its proximity to major lignite coal mining operations.
  • D. Leskovac
    Leskovac is a city in southern Serbia known historically for its textile industry and its popular grilled meat (roštilj) festival.
  • E. Krasin
    Krasin is a historic Russian icebreaker, originally launched in the early 20th century, renowned for Arctic exploration and rescue 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: Kosor
Triple: [Jadranka Kosor, familyName, Kosor]
Generated description
Kosor is a Croatian surname most notably borne by Jadranka Kosor, a former Prime Minister of Croatia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kosor
Target entity description: Kosor is a Croatian surname most notably borne by Jadranka Kosor, a former Prime Minister of Croatia.
  • A. Zala
    Zala is a river in western Hungary that flows into Lake Balaton and lends its name to the surrounding Zala region.
  • B. Moslavina
    Moslavina is a historical and geographical region in central Croatia known for its rural landscapes, vineyards, and small towns.
  • C. Vreoci
    Vreoci is a suburban settlement in the Lazarevac municipality of Belgrade, Serbia, known for its proximity to major lignite coal mining operations.
  • D. Leskovac
    Leskovac is a city in southern Serbia known historically for its textile industry and its popular grilled meat (roštilj) festival.
  • E. Krasin
    Krasin is a historic Russian icebreaker, originally launched in the early 20th century, renowned for Arctic exploration and rescue 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_69d8dd025c188190a1d81f5b4ec7e2c6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6aac4dc8190ac51f22c13f1b96c completed April 20, 2026, 7:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05be4e6e048190b5b0050b90a4ce04 completed May 14, 2026, 12:21 p.m.
NEDg Description generation batch_6a05bf11e17c81909ccc56bd6337d524 completed May 14, 2026, 12:24 p.m.
NED2 Entity disambiguation (via description) batch_6a05bf9b18788190aae5a577b8f725fc completed May 14, 2026, 12:27 p.m.
Created at: April 10, 2026, 12:02 p.m.