Triple

T9703624
Position Surface form Disambiguated ID Type / Status
Subject Pest County E234839 entity
Predicate hasSettlement P1068 FINISHED
Object Vecsés
Vecsés is a town in central Hungary, located near Budapest and known for its proximity to Budapest Ferenc Liszt International Airport.
 E815466 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: Vecsés | Statement: [Pest County, hasSettlement, Vecsés]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vecsés
Context triple: [Pest County, hasSettlement, Vecsés]
  • A. Vilmos
    Vilmos is a masculine given name of Hungarian origin, equivalent to William in English.
  • B. Sarolt
    Sarolt was a prominent 10th-century Hungarian noblewoman and duchess, influential in the Christianization and early state formation of Hungary as the wife of Grand Prince Géza and mother of King Stephen I.
  • C. Teleki
    Teleki is a Hungarian noble family name most notably associated with Pál Teleki, a geographer and two-time prime minister of Hungary in the early 20th century.
  • D. Béla
    Béla was a common medieval Hungarian royal given name borne by several kings, most notably Béla IV of Hungary.
  • E. Hadár
    Hadár is the guiding motto of the Betar youth movement, emphasizing Jewish pride, dignity, and disciplined self-respect.
  • 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: Vecsés
Triple: [Pest County, hasSettlement, Vecsés]
Generated description
Vecsés is a town in central Hungary, located near Budapest and known for its proximity to Budapest Ferenc Liszt International Airport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vecsés
Target entity description: Vecsés is a town in central Hungary, located near Budapest and known for its proximity to Budapest Ferenc Liszt International Airport.
  • A. Vilmos
    Vilmos is a masculine given name of Hungarian origin, equivalent to William in English.
  • B. Sarolt
    Sarolt was a prominent 10th-century Hungarian noblewoman and duchess, influential in the Christianization and early state formation of Hungary as the wife of Grand Prince Géza and mother of King Stephen I.
  • C. Teleki
    Teleki is a Hungarian noble family name most notably associated with Pál Teleki, a geographer and two-time prime minister of Hungary in the early 20th century.
  • D. Béla
    Béla was a common medieval Hungarian royal given name borne by several kings, most notably Béla IV of Hungary.
  • E. Hadár
    Hadár is the guiding motto of the Betar youth movement, emphasizing Jewish pride, dignity, and disciplined self-respect.
  • 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_69ca84cc78808190a56f3402b7c139a7 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d73a0148190ad4178fd462cdd9c completed April 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19132687c8190baf3a60af1b789a8 completed April 4, 2026, 10:31 p.m.
NEDg Description generation batch_69d193150c00819080ed0fbb050b60bf completed April 4, 2026, 10:39 p.m.
NED2 Entity disambiguation (via description) batch_69d19416efd48190865d0178e5e893fa completed April 4, 2026, 10:43 p.m.
Created at: March 30, 2026, 8:18 p.m.