Triple

T2841083
Position Surface form Disambiguated ID Type / Status
Subject Sedibeng District Municipality E62468 entity
Predicate administers P123 FINISHED
Object Heidelberg E332259 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: Heidelberg | Statement: [Sedibeng District Municipality, administers, Heidelberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heidelberg
Context triple: [Sedibeng District Municipality, administers, Heidelberg]
  • A. 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.
  • B. Heidelberg chosen
    Heidelberg is a suburb of Melbourne, Australia, known for its historic role in Australian Impressionism and its location along the Yarra River.
  • C. 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.
  • D. Tübingen
    Tübingen is a historic university town in southwestern Germany known for its well-preserved medieval old town and prestigious Eberhard Karls University.
  • E. Heilbronn
    Heilbronn is a city in the German state of Baden-Württemberg known for its industrial base, wine production, and role as a regional economic and educational hub.
  • 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf16d0c08190bb8de4a4160b4414 completed March 7, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69be67a122ac81909843cd58f3f8f08d completed March 21, 2026, 9:40 a.m.
Created at: March 6, 2026, 10:01 p.m.