Triple

T1070331
Position Surface form Disambiguated ID Type / Status
Subject Erzhausen E23310 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Weiterstadt E188118 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: Weiterstadt | Statement: [Erzhausen, hasNeighbouringMunicipality, Weiterstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weiterstadt
Context triple: [Erzhausen, hasNeighbouringMunicipality, Weiterstadt]
  • A. Weiterstadt chosen
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • B. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • C. Genthin
    Genthin is a small town in the German state of Saxony-Anhalt, historically part of Prussia and known for its location along the Elbe–Havel Canal.
  • D. Hermsdorf
    Hermsdorf is a residential locality in the Berlin borough of Reinickendorf, known for its green surroundings and village-like character on the city’s northern edge.
  • E. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • 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_69a493ee1f908190992b5f0d1b04459b completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b914b4908190886d6698294c6b5b completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad718263f08190b0f03d583abdad10 completed March 8, 2026, 12:54 p.m.
Created at: March 1, 2026, 7:42 p.m.