Triple

T2094750
Position Surface form Disambiguated ID Type / Status
Subject Fejér County E32753 entity
Predicate containsTown P847 FINISHED
Object Velence E137984 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: Velence | Statement: [Fejér County, containsTown, Velence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Velence
Context triple: [Fejér County, containsTown, Velence]
  • A. Velence chosen
    Velence is a Hungarian town and popular resort destination on the shores of Lake Velence, known for its beaches, thermal waters, and recreational tourism.
  • B. Donuzlav
    Donuzlav is a deep-water lagoon and naval harbor in western Crimea that serves as a strategic base for Russian Black Sea naval operations.
  • C. Shipki La
    Shipki La is a high-altitude mountain pass on the India–China (Tibet) border in the Himalayas, serving as an important trade and transit route between the two countries.
  • D. Basovizza
    Basovizza is a village near Trieste in northeastern Italy known for hosting major scientific facilities and for its historical significance in the region.
  • E. Savski Venac
    Savski Venac is a central urban municipality of Belgrade, Serbia, known for its government institutions, major transport hubs, and historic neighborhoods.
  • 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_69a885eba0708190999696a45cbec816 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abba99ddc48190bb2097b56efb7aca completed March 7, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae305cb77c819085c4f3eb2223f749 completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:43 p.m.