Triple

T9196913
Position Surface form Disambiguated ID Type / Status
Subject Ostallgäu E220737 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd87d6460819097234b5dd3f749b4 completed April 1, 2026, 8:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c3b1af48190bb03af15232c510d completed April 4, 2026, 12:32 a.m.
Created at: March 30, 2026, 7:25 p.m.