Triple

T14888359
Position Surface form Disambiguated ID Type / Status
Subject Budapest Metro Line 3 E359687 entity
Predicate terminusSouth P1866 FINISHED
Object Kőbánya-Kispest E354805 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: Kőbánya-Kispest | Statement: [Budapest Metro Line 3, terminusSouth, Kőbánya-Kispest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kőbánya-Kispest
Context triple: [Budapest Metro Line 3, terminusSouth, Kőbánya-Kispest]
  • A. Kőbánya-Kispest chosen
    Kőbánya-Kispest is a major transport hub in Budapest that serves as the southeastern terminus of Metro Line M3 and connects metro, suburban rail, and numerous bus services.
  • B. Józsefváros
    Józsefváros is a central district of Budapest, Hungary, known for its historic urban neighborhoods and ongoing revitalization.
  • C. Budapest II District
    Budapest II District is a largely residential, affluent district on the Buda side of Hungary’s capital, known for its hilly terrain, green areas, and upscale neighborhoods.
  • 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. Kőbánya district
    Kőbánya district is a largely residential and industrial district in southeastern Budapest, Hungary, known for its working-class character and extensive public transport connections.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded5f6cf5c8190b6b28f58fafe5d59 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b5f22c08190a9530cbd78cfc801 completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 2:08 a.m.