Triple

T4315621
Position Surface form Disambiguated ID Type / Status
Subject Schwalm-Eder region E94182 entity
Predicate borderingMajorCity P15361 FINISHED
Object Kassel E210960 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: Kassel | Statement: [Schwalm-Eder region, borderingMajorCity, Kassel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kassel
Context triple: [Schwalm-Eder region, borderingMajorCity, Kassel]
  • A. Kassel chosen
    Kassel is a city in central Germany known for its cultural institutions and as the host of the renowned contemporary art exhibition documenta.
  • B. Gießen
    Gießen is a mid-sized university city in central Germany known for its academic institutions and role as a regional administrative and cultural center.
  • C. Erfurt
    Erfurt is a historic German city in the state of Thuringia, known for its well-preserved medieval old town and as an important cultural and educational center.
  • D. Wetzlar
    Wetzlar is a historic German city in the state of Hesse, known for its medieval old town and its long tradition in optics and precision engineering.
  • E. Karlsruhe
    Karlsruhe is a major city in southwestern Germany best known as the seat of the country’s highest courts and a central hub of German constitutional jurisprudence.
  • 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_69b3451886588190a3dd1305ea7c58dc completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b350f60dfc819098202b7eb3bbf402 completed March 12, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20ce295f081909046cbc278ee6183 completed March 24, 2026, 4:02 a.m.
Created at: March 12, 2026, 11:12 p.m.