Triple

T17014018
Position Surface form Disambiguated ID Type / Status
Subject Őrség E412770 entity
Predicate containsSettlement P847 FINISHED
Object Velemér
Velemér is a small village in western Hungary known for its historic medieval church and frescoes, situated in the rural Őrség region.
 E1247041 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: Velemér | Statement: [Őrség, containsSettlement, Velemér]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Velemér
Context triple: [Őrség, containsSettlement, Velemér]
  • A. Vrély
    Vrély is a small rural commune in the Somme department of northern France.
  • B. Vít
    Vít is a Czech given name derived from the Latin name Vitus, commonly used in Czech-speaking countries.
  • C. Drostán
    Drostán is an alternative name for Saint Drostan, an early Scottish abbot and missionary associated with the Christianization of northeastern Scotland.
  • D. Vesemir
    Vesemir is an experienced and wise witcher of the School of the Wolf who serves as a mentor and father figure to Geralt of Rivia in The Witcher series.
  • E. Vladimirci
    Vladimirci is a small town and municipality in western Serbia, situated in the Mačva region and known for its agricultural surroundings.
  • 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: Velemér
Triple: [Őrség, containsSettlement, Velemér]
Generated description
Velemér is a small village in western Hungary known for its historic medieval church and frescoes, situated in the rural Őrség region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Velemér
Target entity description: Velemér is a small village in western Hungary known for its historic medieval church and frescoes, situated in the rural Őrség region.
  • A. Vrély
    Vrély is a small rural commune in the Somme department of northern France.
  • B. Vít
    Vít is a Czech given name derived from the Latin name Vitus, commonly used in Czech-speaking countries.
  • C. Drostán
    Drostán is an alternative name for Saint Drostan, an early Scottish abbot and missionary associated with the Christianization of northeastern Scotland.
  • D. Vesemir
    Vesemir is an experienced and wise witcher of the School of the Wolf who serves as a mentor and father figure to Geralt of Rivia in The Witcher series.
  • E. Vladimirci
    Vladimirci is a small town and municipality in western Serbia, situated in the Mačva region and known for its agricultural surroundings.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47e64f081908f43870c7564d0ae completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b4990948190861ff81f8fc3e8f2 completed May 10, 2026, 11:56 p.m.
NEDg Description generation batch_6a011cc1afc48190b83e3203407c1d7f completed May 11, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_6a011d67c82c8190b737406e8952eb2b completed May 11, 2026, 12:05 a.m.
Created at: April 10, 2026, 5:33 a.m.