Triple

T14902280
Position Surface form Disambiguated ID Type / Status
Subject Hármashatár-hegy E360034 entity
Predicate near P350 FINISHED
Object Óbuda E349572 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: Óbuda | Statement: [Hármashatár-hegy, near, Óbuda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Óbuda
Context triple: [Hármashatár-hegy, near, Óbuda]
  • A. Óbuda chosen
    Óbuda is a historic district in present-day Budapest, Hungary, known as one of the city’s oldest inhabited areas and a former independent town before its unification with Buda and Pest.
  • B. Okuku
    Okuku is a town in Osun State, southwestern Nigeria, situated near the city of Ikirun.
  • C. Ubakala
    Ubakala is a town in Abia State, southeastern Nigeria, serving as the administrative center of the Umuahia South Local Government Area.
  • D. Goba
    Goba is a small Ethiopian town in the Oromia Region that serves as a primary gateway and service center for visitors to Bale Mountains National Park.
  • E. Binya
    Binya is a small rural locality in New South Wales, Australia, situated in an agricultural region of the Riverina.
  • 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_69ded60b24008190bd272c0d61329400 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe72b4e4f88190af7e859d93dbbd28 completed May 8, 2026, 11:33 p.m.
Created at: April 10, 2026, 2:11 a.m.