Triple

T13536634
Position Surface form Disambiguated ID Type / Status
Subject Eiserner Steg E323278 entity
Predicate connects P390 FINISHED
Object Sachsenhausen E131173 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: Sachsenhausen | Statement: [Eiserner Steg, connects, Sachsenhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sachsenhausen
Context triple: [Eiserner Steg, connects, Sachsenhausen]
  • A. Sachsenhausen chosen
    Sachsenhausen is a historic and culturally vibrant district of Frankfurt am Main, known for its traditional apple wine taverns, museums, and picturesque old town streets.
  • B. Sachsenhausen
    Sachsenhausen is a district or neighborhood within the town of Giengen an der Brenz in the German state of Baden-Württemberg.
  • C. Spandau
    Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
  • D. Sachsenhausen district
    The Sachsenhausen district is a historic quarter of Frankfurt am Main, Germany, known for its traditional apple wine taverns, cobbled streets, and vibrant nightlife along the south bank of the Main River.
  • E. Neu-Hohenschönhausen
    Neu-Hohenschönhausen is a residential locality in the northeast of Berlin, known for its large prefabricated housing estates and post-war urban development.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafbe39948190808062d4eff91841 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0d759fc81908c327850a4836ecd completed May 3, 2026, 9:40 p.m.
Created at: April 9, 2026, 9:45 p.m.