Triple

T301836
Position Surface form Disambiguated ID Type / Status
Subject Herrlingen cemetery E6212 entity
Predicate locatedNear P294 FINISHED
Object Ulm E9969 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: Ulm | Statement: [Herrlingen cemetery, locatedNear, Ulm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ulm
Context triple: [Herrlingen cemetery, locatedNear, Ulm]
  • A. Ulm chosen
    Ulm is a historic city in the German state of Baden-Württemberg, best known for its towering Gothic cathedral and as the birthplace of physicist Albert Einstein.
  • B. 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.
  • C. Stuttgart
    Stuttgart is a major city in southwestern Germany known as an important industrial, cultural, and economic center, particularly famous for its automotive industry and surrounding wine-growing region.
  • D. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • E. Heidelberg
    Heidelberg is a historic university city in southwestern Germany renowned for its picturesque old town, castle ruins, and one of Europe’s oldest universities.
  • 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_69a2e79230508190b912ecb555aae17e completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ea0dd1dc8190aecd5afdeb2fd74b completed Feb. 28, 2026, 1:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1cc7fc6c8190ac5da1e473396932 completed March 7, 2026, 12:40 p.m.
Created at: Feb. 28, 2026, 1:06 p.m.