Triple

T4006054
Position Surface form Disambiguated ID Type / Status
Subject Rhine-Main metropolitan region E89528 entity
Predicate majorCity P316 FINISHED
Object Hanau E289017 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: Hanau | Statement: [Rhine-Main metropolitan region, majorCity, Hanau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanau
Context triple: [Rhine-Main metropolitan region, majorCity, Hanau]
  • A. Hanau chosen
    Hanau is a town in the German state of Hesse, known as an important regional center and the birthplace of the Brothers Grimm.
  • B. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • C. Gehrden
    Gehrden is a small town in Lower Saxony, Germany, located near Hanover and known for its surrounding rural villages and scenic landscapes.
  • D. Herrlingen
    Herrlingen is a small village in the German state of Baden-Württemberg, historically noted as the place where Field Marshal Erwin Rommel spent his final days during World War II.
  • E. Aichach-Friedberg
    Aichach-Friedberg is a rural district in the Bavarian administrative region of Swabia in southern Germany, known for its small towns, agricultural landscape, and proximity to Augsburg.
  • 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa60c500819084fcba785b2bf801 completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5629004208190964cb4d2e75b0a05 completed March 14, 2026, 1:28 p.m.
Created at: March 9, 2026, 3:34 p.m.