Triple

T14445991
Position Surface form Disambiguated ID Type / Status
Subject River Havel E358205 entity
Predicate connectedTo P37 FINISHED
Object Jungfernsee E161906 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: Jungfernsee | Statement: [River Havel, connectedTo, Jungfernsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jungfernsee
Context triple: [River Havel, connectedTo, Jungfernsee]
  • A. Jungfernsee chosen
    Jungfernsee is a scenic lake on the outskirts of Potsdam and Berlin, known for its historic villas, palaces, and location along the former inner German border.
  • B. Königssee
    Königssee is a picturesque alpine lake in southeastern Germany, renowned for its emerald-green waters, steep surrounding mountains, and status as one of the cleanest lakes in the country.
  • C. Grunewaldsee
    Grunewaldsee is a popular forest lake in Berlin known for its scenic surroundings and dog-friendly bathing areas.
  • D. Scharmützelsee
    Scharmützelsee is a popular lake in eastern Germany known for its scenic surroundings, recreational activities, and spa resorts.
  • E. Alpsee
    Alpsee is a picturesque alpine lake in Bavaria, Germany, renowned for its clear waters and scenic setting near the royal castles of Neuschwanstein and Hohenschwangau.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de915e76f481909fe9462f964b5b1c completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd648d8904819084d720a0fd2ddb4b completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:19 a.m.