Triple

T624980
Position Surface form Disambiguated ID Type / Status
Subject Reinickendorf E14596 entity
Predicate containsPartOf P1393 FINISHED
Object Lake Tegel shoreline E78856 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 Tegel shoreline | Statement: [Reinickendorf, containsPartOf, Lake Tegel shoreline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Tegel shoreline
Context triple: [Reinickendorf, containsPartOf, Lake Tegel shoreline]
  • A. Lake Tegel chosen
    Lake Tegel is a large lake in the northwest of Berlin, Germany, known for its recreational areas, beaches, and surrounding forests.
  • B. Turtle Pond
    Turtle Pond is a small, tranquil body of water in New York City's Central Park known for its resident turtles and scenic views near Belvedere Castle.
  • C. Alster
    The Alster is a river and series of lakes in Hamburg, Germany, that form a central recreational and scenic landmark of the city.
  • D. The Lake
    The Lake is a village-like neighborhood in Newton, Massachusetts, known for its strong community identity and historically Irish-American roots.
  • E. The Lake
    The Lake is a picturesque man-made body of water in New York City's Central Park, popular for boating, scenic views, and surrounding walking paths.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e43002c81908e0c7dab29b75978 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a56c4b64088190a033462dd923f5b2 completed March 2, 2026, 10:54 a.m.
Created at: March 1, 2026, 7:35 p.m.