Triple

T3688915
Position Surface form Disambiguated ID Type / Status
Subject Bode E78295 entity
Predicate flowsThrough P225 FINISHED
Object Staßfurt E401699 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: Staßfurt | Statement: [Bode, flowsThrough, Staßfurt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Staßfurt
Context triple: [Bode, flowsThrough, Staßfurt]
  • A. Suhl
    Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
  • B. Nordhausen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • C. Stendal chosen
    Stendal is a historic town in the German state of Saxony-Anhalt, known as a regional cultural center and the birthplace of art historian Johann Joachim Winckelmann.
  • D. Neustadt an der Aisch
    Neustadt an der Aisch is a small town in the Bavarian region of Germany, known for its historic center and location along the Aisch River between Würzburg and Nuremberg.
  • E. Seligenstadt
    Seligenstadt is a historic town in Hesse, Germany, known for its well-preserved medieval center and its association with the Carolingian scholar Einhard.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4c960788190b73ede08658846aa completed March 8, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdb8e6b8848190a2b7951638f53465 completed March 20, 2026, 9:15 p.m.
Created at: March 8, 2026, 3:26 p.m.