Triple

T1582149
Position Surface form Disambiguated ID Type / Status
Subject Westphalia E33788 entity
Predicate contains P35 FINISHED
Object Bielefeld E279260 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: Bielefeld | Statement: [Westphalia, contains, Bielefeld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bielefeld
Context triple: [Westphalia, contains, Bielefeld]
  • A. Bielefeld chosen
    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.
  • B. Osnabrück
    Osnabrück is a historic city in Lower Saxony, Germany, known for its medieval architecture and role in the Peace of Westphalia.
  • C. Paderborn
    Paderborn is a historic city in western Germany known for its medieval cathedral, role as a regional religious and cultural center, and strategic importance during World War II.
  • D. Braunschweig
    Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
  • E. Detmold
    Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
  • 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_69a885f27a4c8190a4622252cdf54c00 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908ef80a48190bd5a8e51c65e5588 completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69b54c0e702081909384b804fb1ade90 completed March 14, 2026, 11:52 a.m.
Created at: March 4, 2026, 7:27 p.m.