Triple

T6213055
Position Surface form Disambiguated ID Type / Status
Subject Lippe E138916 entity
Predicate capital P234 FINISHED
Object Detmold E269423 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: Detmold | Statement: [Lippe, capital, Detmold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Detmold
Context triple: [Lippe, capital, Detmold]
  • A. Detmold chosen
    Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
  • B. Lippstadt
    Lippstadt is a historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and role in regional conflicts.
  • C. Meppen
    Meppen is a historic town in Lower Saxony, Germany, known as a regional center in the Emsland district near the Dutch border.
  • D. Bielefeld
    Bielefeld is a major city in northwestern Germany known for its industrial heritage, university, and the tongue-in-cheek “Bielefeld conspiracy” meme claiming it does not exist.
  • E. Iserlohn
    Iserlohn is a city in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known historically for its role in World War II and its metalworking and industrial heritage.
  • 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_69c008ada364819096c9e92c74d639b5 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0628c52ec8190b9c62c7fdc0aa83b completed March 22, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c91f3e6cec8190ad66e8f4feb6b911 completed March 29, 2026, 12:46 p.m.
Created at: March 22, 2026, 4:21 p.m.