Triple

T14902487
Position Surface form Disambiguated ID Type / Status
Subject Pilis Mountains E360039 entity
Predicate hasSettlementNearby P7611 FINISHED
Object Pilisvörösvár E887087 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: Pilisvörösvár | Statement: [Pilis Mountains, hasSettlementNearby, Pilisvörösvár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pilisvörösvár
Context triple: [Pilis Mountains, hasSettlementNearby, Pilisvörösvár]
  • A. Pilisvörösvár chosen
    Pilisvörösvár is a town in central Hungary known for its German minority heritage and proximity to Budapest.
  • B. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • C. Pécsvárad
    Pécsvárad is a small historic town in southern Hungary known for its medieval abbey and scenic setting near the Mecsek Mountains.
  • D. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • E. Balvanyos
    Balvanyos is a Romanian mountain resort area known for its natural mineral springs, spa facilities, and scenic surroundings in the Eastern Carpathians.
  • 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_69feb7d554808190a0a87d9f5e225d31 completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 2:11 a.m.