Triple

T4247274
Position Surface form Disambiguated ID Type / Status
Subject Neues Museum E95558 entity
Predicate nearbyLandmark P350 FINISHED
Object Lustgarten E106565 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: Lustgarten | Statement: [Neues Museum, nearbyLandmark, Lustgarten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lustgarten
Context triple: [Neues Museum, nearbyLandmark, Lustgarten]
  • A. Lustgarten chosen
    Lustgarten is a historic public park and square on Berlin’s Museum Island, long used as a parade ground and gathering place.
  • B. Riedergarten
    Riedergarten is a historic public garden and popular green oasis located in the Bavarian city of Rosenheim, Germany.
  • C. Schöngarth
    Schöngarth is a German surname most notably associated with Eberhard Schöngarth, a high-ranking Nazi SS officer and war criminal during World War II.
  • D. Haldenstein
    Haldenstein is a small Swiss village in the canton of Graubünden, known in architecture circles as the longtime base of renowned architect Peter Zumthor.
  • E. Vogelthal
    Vogelthal is a small village in Bavaria, Germany, known as the birthplace of World War II tank commander Michael Wittmann.
  • 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_69b3453d91548190b4d4ef8fe52aa2ac completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e9b64ac81908dc44eaae6829b50 completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a87c033881908e0cf9fdfecaf36a completed March 14, 2026, 6:27 p.m.
Created at: March 12, 2026, 11:05 p.m.