Triple

T1204137
Position Surface form Disambiguated ID Type / Status
Subject Lake Velence E25848 entity
Predicate hasShoreSettlement P16159 FINISHED
Object Velence E137984 NE FINISHED

How this triple was built (3 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: [Lake Velence, hasShoreSettlement, Velence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Velence
Context triple: [Lake Velence, hasShoreSettlement, 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. Savski Venac
    Savski Venac is a central urban municipality of Belgrade, Serbia, known for its government institutions, major transport hubs, and historic neighborhoods.
  • E. Czarna Góra
    Czarna Góra is a village in southern Poland, known as a mountain resort area in the Tatra region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasShoreSettlement
Context triple: [Lake Velence, hasShoreSettlement, Velence]
  • A. hasShoreFeature
    Indicates that a shore or coastline possesses a specific physical or environmental feature.
  • B. hasHumanSettlement chosen
    Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
  • C. hasCityOnShore
    Indicates that a city is located on or directly adjacent to the shore of a body of water.
  • D. hasIsland
    Indicates that one entity possesses, contains, or includes an island as part of its domain, territory, or structure.
  • E. hasIslandNearby
    Indicates that one location is situated close to an island in geographic space.
  • F. None of above.

Provenance (4 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_69a4942b30f08190a91c60573e16b5ef completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bdbf94188190991f63a84cc76b8a completed March 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8a08e1a881908b3f3a41cc1fb010 completed March 7, 2026, 8:26 p.m.
PD Predicate disambiguation batch_69a4bb5ed2b88190aab992913957e1cf completed March 1, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:46 p.m.