Triple

T20135888
Position Surface form Disambiguated ID Type / Status
Subject Red line (Stockholm metro) E491023 entity
Predicate passesThroughStation P3947 FINISHED
Object Zinkensdamm NE NERFINISHED

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: Zinkensdamm | Statement: [Red line (Stockholm metro), passesThroughStation, Zinkensdamm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zinkensdamm
Context triple: [Red line (Stockholm metro), passesThroughStation, Zinkensdamm]
  • A. Zinkensdamm chosen
    Zinkensdamm is a residential and recreational area in Stockholm known for its sports grounds, park spaces, and location on the island district of Södermalm.
  • B. Hohenwarte Dam
    Hohenwarte Dam is a large hydroelectric and flood-control dam on the Saale River in Thuringia, Germany, forming one of the country’s significant reservoir lakes.
  • C. Schwelm Dam
    Schwelm Dam is a German reservoir dam that was one of the targets attacked during the World War II Dambusters Raid.
  • D. Diemel Dam
    Diemel Dam is a German reservoir dam that was one of the targets attacked during the World War II Dambusters Raid.
  • E. Ballindamm
    Ballindamm is a prominent boulevard in central Hamburg, Germany, known for its upscale shops, offices, and views over the Binnenalster lake.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66766e46c81908721fd47066dc9f8 completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:32 p.m.