Triple

T23124859
Position Surface form Disambiguated ID Type / Status
Subject Main-Kinzig-Kreis E576998 entity
Predicate contains P35 FINISHED
Object Steinau an der Straße E809185 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: Steinau an der Straße | Statement: [Main-Kinzig-Kreis, contains, Steinau an der Straße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steinau an der Straße
Context triple: [Main-Kinzig-Kreis, contains, Steinau an der Straße]
  • A. Steinau an der Straße chosen
    Steinau an der Straße is a historic small town in Hesse, Germany, best known for its association with the Brothers Grimm and its well-preserved medieval architecture.
  • B. Steinheim
    Steinheim is a locality within the Bavarian town of Dillingen an der Donau in southern Germany.
  • C. Steinbühl
    Steinbühl is a district of the German city of Nuremberg, known as an urban residential area served by the Nürnberg-Steinbühl railway station.
  • D. Friedrichstein
    Friedrichstein is a district or neighborhood within the spa town of Bad Wildungen in the state of Hesse, Germany.
  • E. Günterstal
    Günterstal is a district of Freiburg im Breisgau in southwestern Germany, known for its scenic valley setting in the Black Forest and historic monastery.
  • 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_69e245f6c2e881909a228fdcfeb7c7d3 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e53ac288190b27fe8064fb576c2 completed April 29, 2026, 4:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c23f25dec8190984bc2dafd008a48 completed May 19, 2026, 8:48 a.m.
Created at: April 17, 2026, 3:59 p.m.