Triple

T17013962
Position Surface form Disambiguated ID Type / Status
Subject Vas County E412769 entity
Predicate containsSettlement P847 FINISHED
Object Őriszentpéter
Őriszentpéter is a small historic town in western Hungary, known as a gateway to the Őrség National Park and for its traditional rural architecture and natural surroundings.
 E1247032 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: Őriszentpéter | Statement: [Vas County, containsSettlement, Őriszentpéter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Őriszentpéter
Context triple: [Vas County, containsSettlement, Őriszentpéter]
  • A. Pázmány
    Pázmány is a Hungarian surname most notably associated with the influential 17th-century Jesuit cardinal and statesman Péter Pázmány.
  • B. Sebestyén
    Sebestyén is a Hungarian surname most notably borne by architect Artúr Sebestyén.
  • C. Szenttamás
    Szenttamás is the Hungarian name for the town of Srbobran in northern Serbia, located in the autonomous province of Vojvodina.
  • D. Pál
    Pál is a Hungarian given name, equivalent to the English name Paul.
  • E. Saint Gellért
    Saint Gellért (Saint Gerard of Csanád) was an 11th-century Italian-born Benedictine monk and bishop who became one of Hungary’s earliest Christian missionaries and martyrs, later venerated as a national patron saint.
  • 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: Őriszentpéter
Triple: [Vas County, containsSettlement, Őriszentpéter]
Generated description
Őriszentpéter is a small historic town in western Hungary, known as a gateway to the Őrség National Park and for its traditional rural architecture and natural surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Őriszentpéter
Target entity description: Őriszentpéter is a small historic town in western Hungary, known as a gateway to the Őrség National Park and for its traditional rural architecture and natural surroundings.
  • A. Pázmány
    Pázmány is a Hungarian surname most notably associated with the influential 17th-century Jesuit cardinal and statesman Péter Pázmány.
  • B. Sebestyén
    Sebestyén is a Hungarian surname most notably borne by architect Artúr Sebestyén.
  • C. Szenttamás
    Szenttamás is the Hungarian name for the town of Srbobran in northern Serbia, located in the autonomous province of Vojvodina.
  • D. Pál
    Pál is a Hungarian given name, equivalent to the English name Paul.
  • E. Saint Gellért
    Saint Gellért (Saint Gerard of Csanád) was an 11th-century Italian-born Benedictine monk and bishop who became one of Hungary’s earliest Christian missionaries and martyrs, later venerated as a national patron saint.
  • 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.