Triple

T8583199
Position Surface form Disambiguated ID Type / Status
Subject Gusztáv Jány E203235 entity
Predicate placeOfDeath P21 FINISHED
Object Budapest, Hungary E13406 NE FINISHED

How this triple was built (2 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: Budapest, Hungary | Statement: [Gusztáv Jány, placeOfDeath, Budapest, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Budapest, Hungary
Context triple: [Gusztáv Jány, placeOfDeath, Budapest, Hungary]
  • A. Budapest chosen
    Budapest is the capital and largest city of Hungary, renowned for its historic architecture, thermal baths, and prominent location along the Danube River.
  • B. Budaörs, Hungary
    Budaörs is a suburban town just west of Budapest in Hungary, known for its rapid post-communist development, commercial centers, and role as a key transport hub near the capital.
  • C. Kaposvár, Hungary
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • D. Budaörs
    Budaörs is a suburban town near Budapest in Hungary, known for its rapid post-communist development and role as a commercial and residential hub.
  • E. Siófok
    Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8329bb7c8190a63c643730839103 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbeb1d0edc8190b4495935275252f3 completed March 31, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d016e84df4819092b442216a5f6c9e completed April 3, 2026, 7:37 p.m.
Created at: March 30, 2026, 6:22 p.m.