Triple

T13846397
Position Surface form Disambiguated ID Type / Status
Subject Hron River E332816 entity
Predicate mouthLocation P417 FINISHED
Object Esztergom E175407 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: Esztergom | Statement: [Hron River, mouthLocation, Esztergom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Esztergom
Context triple: [Hron River, mouthLocation, Esztergom]
  • A. Esztergom chosen
    Esztergom is a historic Hungarian city on the Danube River that served as an early royal capital and remains a major religious and cultural center.
  • B. Gödöllő
    Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
  • C. Budavár
    Budavár is the historic Buda Castle quarter of Budapest, known for its medieval streets, royal palace complex, and panoramic views over the Danube.
  • 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. Székesfehérvár
    Székesfehérvár is a historic city in central Hungary that served as a medieval royal seat and coronation site for Hungarian kings.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02b1a25c8190a9f85ba43c421188 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2189c1cc819080dc296b17e42374 completed May 9, 2026, 11:59 a.m.
Created at: April 9, 2026, 10:13 p.m.