Triple

T15347420
Position Surface form Disambiguated ID Type / Status
Subject Ferenc Münnich E366958 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: [Ferenc Münnich, placeOfDeath, Budapest, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Budapest, Hungary
Context triple: [Ferenc Münnich, 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. Újbuda
    Újbuda is a major residential and commercial district on the Buda side of Budapest, known for its universities, cultural venues, and riverside areas along the Danube.
  • E. 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.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e1749bc8190a8b9cbcb27288a5b completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff755ffbdc8190825010885e68ebc3 completed May 9, 2026, 5:56 p.m.
Created at: April 10, 2026, 3:17 a.m.