Triple

T12856468
Position Surface form Disambiguated ID Type / Status
Subject Lady Mary Victoria Hamilton E307467 entity
Predicate residence P75 FINISHED
Object Keszthely E168264 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: Keszthely | Statement: [Lady Mary Victoria Hamilton, residence, Keszthely]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keszthely
Context triple: [Lady Mary Victoria Hamilton, residence, Keszthely]
  • A. Keszthely chosen
    Keszthely is a historic town in western Hungary known for its lakeside resort atmosphere, cultural heritage, and proximity to Lake Balaton.
  • B. Dunakeszi
    Dunakeszi is a town in Hungary located just north of Budapest, known as a rapidly growing suburban and commuter settlement along the Danube in Pest County.
  • C. Nagykőrös
    Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
  • D. Tihany
    Tihany is a historic village on the northern shore of Lake Balaton in Hungary, renowned for its Benedictine abbey, scenic peninsula, and traditional architecture.
  • E. Kiskőrös
    Kiskőrös is a small town in southern Hungary known as the birthplace of the national poet Sándor Petőfi and for its wine-producing region.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970231ce48190a4eabc4b8c24a3ff completed April 10, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d6d4bd8819087902472e77e0d38 completed May 8, 2026, 4:58 a.m.
Created at: April 9, 2026, 5:37 p.m.