Triple

T9006737
Position Surface form Disambiguated ID Type / Status
Subject Ostallgäu E215162 entity
Predicate contains P35 FINISHED
Object Forggensee E209090 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: Forggensee | Statement: [Ostallgäu, contains, Forggensee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Forggensee
Context triple: [Ostallgäu, contains, Forggensee]
  • A. Forggensee chosen
    Forggensee is a large artificial lake in Bavaria, Germany, popular for boating and scenic views of the surrounding Alps and nearby castles.
  • B. Bad Waldsee
    Bad Waldsee is a historic spa town in the German state of Baden-Württemberg, known for its thermal baths and picturesque old town.
  • C. Scharmützelsee
    Scharmützelsee is a popular lake in eastern Germany known for its scenic surroundings, recreational activities, and spa resorts.
  • D. Teufelssee
    Teufelssee is a small natural lake in Berlin known for its scenic setting, recreational swimming, and clothing-optional bathing area.
  • E. Geiseltalsee
    Geiseltalsee is a large artificial lake in Saxony-Anhalt, Germany, created by flooding a former lignite mining area and now used for recreation and nature conservation.
  • 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_69ca83a12d648190b1e4fe11e8a31890 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69bc6e208190b0c01e3761c04799 completed April 1, 2026, 12:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd0e7f090819093c7af51c3979978 completed April 3, 2026, 2:38 p.m.
Created at: March 30, 2026, 7:05 p.m.