Triple

T15250942
Position Surface form Disambiguated ID Type / Status
Subject Elbsandsteingebirge E364515 entity
Predicate contains P35 FINISHED
Object Lilienstein E1127273 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: Lilienstein | Statement: [Elbsandsteingebirge, contains, Lilienstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lilienstein
Context triple: [Elbsandsteingebirge, contains, Lilienstein]
  • A. Lilienstein chosen
    Lilienstein is a prominent table mountain in Saxon Switzerland, Germany, known for its striking flat-topped silhouette above the Elbe River.
  • B. Tettenweis
    Tettenweis is a small Bavarian village in Germany known as the birthplace of the Symbolist painter Franz von Stuck.
  • C. Lunzenau
    Lunzenau is a small town in the German state of Saxony, known for its location along the Zwickauer Mulde river and its historic architecture.
  • D. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • E. Biesenthal
    Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f728648190b2c86e4528542b65 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff01de4ccc8190aeac4a6c1ffc08d9 completed May 9, 2026, 9:43 a.m.
Created at: April 10, 2026, 3:13 a.m.