Triple

T7517888
Position Surface form Disambiguated ID Type / Status
Subject Disney Sequoia Lodge E177690 entity
Predicate hasView P854 FINISHED
Object Lake Disney E670604 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: Lake Disney | Statement: [Disney Sequoia Lodge, hasView, Lake Disney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Disney
Context triple: [Disney Sequoia Lodge, hasView, Lake Disney]
  • A. Lake Disney chosen
    Lake Disney is an artificial lake at Disneyland Paris, surrounded by several Disney hotels and entertainment venues and used as a scenic focal point for the resort area.
  • B. Lake Flower
    Lake Flower is a small scenic lake in the village of Saranac Lake in New York’s Adirondack Mountains, known for recreation and waterfront views.
  • C. Lake Amadeus
    Lake Amadeus is a large, remote salt lake in Australia’s Northern Territory, notable for its extensive salt flats and proximity to Uluru.
  • D. San Andreas Lake
    San Andreas Lake is a long, narrow reservoir on the San Francisco Peninsula in California, best known for lending its name to the nearby San Andreas Fault.
  • E. Lake Carnegie
    Lake Carnegie is a man-made lake in Princeton, New Jersey, best known as a rowing and recreational waterway associated with Princeton University.
  • 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_69c69f2891148190a484f3b8222c6f1b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5f6ccc8819080ffd123fdd59a50 completed March 27, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84ef834608190bf425f99222a4bc5 completed March 28, 2026, 9:58 p.m.
Created at: March 27, 2026, 3:46 p.m.