Triple

T10290768
Position Surface form Disambiguated ID Type / Status
Subject Binnenalster E241355 entity
Predicate watercourse P415 FINISHED
Object Alster E49041 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: Alster | Statement: [Binnenalster, watercourse, Alster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alster
Context triple: [Binnenalster, watercourse, Alster]
  • A. Alster chosen
    The Alster is a river and series of lakes in Hamburg, Germany, that form a central recreational and scenic landmark of the city.
  • B. Avon Lake
    Avon Lake is a suburban city in northern Ohio situated along the Lake Erie shoreline, known for its residential communities and lakefront parks.
  • C. Silver Lake
    Silver Lake is a scenic recreational lake located within Blackwell Forest Preserve in DuPage County, Illinois.
  • D. Silver Lake
    Silver Lake is a trendy, historically bohemian neighborhood in central Los Angeles known for its reservoir, hillside homes, and vibrant arts, dining, and nightlife scenes.
  • E. Silver Lake
    Silver Lake is a scenic body of water within Lynn Woods Reservation in Lynn, Massachusetts, popular for its natural beauty and outdoor recreation.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2d281348190bac00cf826689cd7 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d1465e88190aaa8b295df3f9c8c completed April 9, 2026, 3:29 a.m.
Created at: April 6, 2026, 11:41 a.m.