Triple

T9096520
Position Surface form Disambiguated ID Type / Status
Subject Zala River E218034 entity
Predicate hasCityOnRiver P17819 FINISHED
Object Zalalövő
Zalalövő is a small town in western Hungary known for its scenic setting near the Zala River and its role as a local administrative and transport hub.
 E777896 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: Zalalövő | Statement: [Zala River, hasCityOnRiver, Zalalövő]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zalalövő
Context triple: [Zala River, hasCityOnRiver, Zalalövő]
  • A. Zagyva
    Zagyva is a river in northern Hungary that flows through towns such as Salgótarján and Hatvan before joining the Tisza River.
  • B. Zengő
    Zengő is a prominent peak in southern Hungary known for its scenic hiking trails and panoramic views over the Mecsek mountain range.
  • C. Neszmély
    Neszmély is a village in northwestern Hungary on the Danube River, historically noted as the place where Holy Roman Emperor Albert II died.
  • D. Zardoz
    Zardoz is a 1974 science fiction film directed by John Boorman, known for its surreal, dystopian vision and starring Sean Connery in one of his most unconventional roles.
  • E. Dunántúl
    Dunántúl is the Hungarian name for Transdanubia, the large western region of Hungary lying west of the Danube River.
  • 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: Zalalövő
Triple: [Zala River, hasCityOnRiver, Zalalövő]
Generated description
Zalalövő is a small town in western Hungary known for its scenic setting near the Zala River and its role as a local administrative and transport hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zalalövő
Target entity description: Zalalövő is a small town in western Hungary known for its scenic setting near the Zala River and its role as a local administrative and transport hub.
  • A. Zagyva
    Zagyva is a river in northern Hungary that flows through towns such as Salgótarján and Hatvan before joining the Tisza River.
  • B. Zengő
    Zengő is a prominent peak in southern Hungary known for its scenic hiking trails and panoramic views over the Mecsek mountain range.
  • C. Neszmély
    Neszmély is a village in northwestern Hungary on the Danube River, historically noted as the place where Holy Roman Emperor Albert II died.
  • D. Zardoz
    Zardoz is a 1974 science fiction film directed by John Boorman, known for its surreal, dystopian vision and starring Sean Connery in one of his most unconventional roles.
  • E. Dunántúl
    Dunántúl is the Hungarian name for Transdanubia, the large western region of Hungary lying west of the Danube River.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc96b7d0d48190a3b15f35bef087e3 completed April 1, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0180f70b88190a2d3dc49f32f0c2e completed April 3, 2026, 7:42 p.m.
NEDg Description generation batch_69d019652fe8819096cccb8cff431261 completed April 3, 2026, 7:47 p.m.
NED2 Entity disambiguation (via description) batch_69d01a290de881909482b7eb70bef0e3 completed April 3, 2026, 7:51 p.m.
Created at: March 30, 2026, 7:15 p.m.