Triple

T14147994
Position Surface form Disambiguated ID Type / Status
Subject District XI of Budapest E350602 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Sashegy (partly)
Sashegy (partly) is a largely residential, hillside neighborhood in Budapest known for its green areas, scenic views, and proximity to the city center.
 E1081663 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: Sashegy (partly) | Statement: [District XI of Budapest, hasNeighbourhood, Sashegy (partly)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sashegy (partly)
Context triple: [District XI of Budapest, hasNeighbourhood, Sashegy (partly)]
  • A. Zagyva
    Zagyva is a river in northern Hungary that flows through towns such as Salgótarján and Hatvan before joining the Tisza River.
  • B. Csonka
    Csonka is a surname most famously associated with Larry Csonka, the Hall of Fame former NFL fullback for the Miami Dolphins.
  • C. Schashagen
    Schashagen is a small municipality in the Ostholstein district of Schleswig-Holstein in northern Germany.
  • D. Sajos
    Sajos is the main cultural and administrative center of the Sámi people in Finland, housing the Sámi Parliament and related institutions in Inari.
  • E. Tarnazsadány
    Tarnazsadány is a small village in northern Hungary, situated within Heves County and characterized by its rural, agricultural setting.
  • 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: Sashegy (partly)
Triple: [District XI of Budapest, hasNeighbourhood, Sashegy (partly)]
Generated description
Sashegy (partly) is a largely residential, hillside neighborhood in Budapest known for its green areas, scenic views, and proximity to the city center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sashegy (partly)
Target entity description: Sashegy (partly) is a largely residential, hillside neighborhood in Budapest known for its green areas, scenic views, and proximity to the city center.
  • A. Zagyva
    Zagyva is a river in northern Hungary that flows through towns such as Salgótarján and Hatvan before joining the Tisza River.
  • B. Csonka
    Csonka is a surname most famously associated with Larry Csonka, the Hall of Fame former NFL fullback for the Miami Dolphins.
  • C. Schashagen
    Schashagen is a small municipality in the Ostholstein district of Schleswig-Holstein in northern Germany.
  • D. Sajos
    Sajos is the main cultural and administrative center of the Sámi people in Finland, housing the Sámi Parliament and related institutions in Inari.
  • E. Tarnazsadány
    Tarnazsadány is a small village in northern Hungary, situated within Heves County and characterized by its rural, agricultural setting.
  • 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_69d827865f608190b311820428ae027b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61237ef481909374c1f68a2370b7 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf205c788190920b5055f9fe63a8 completed May 7, 2026, 6:51 p.m.
NEDg Description generation batch_69fce266b2a08190998f04913064e43f completed May 7, 2026, 7:05 p.m.
NED2 Entity disambiguation (via description) batch_69fce2cd8cb481908e3e5a421e732948 completed May 7, 2026, 7:06 p.m.
Created at: April 10, 2026, 12:55 a.m.