Triple

T13312423
Position Surface form Disambiguated ID Type / Status
Subject Witten E317101 entity
Predicate locatedNear P294 FINISHED
Object Bochum E248839 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: Bochum | Statement: [Witten, locatedNear, Bochum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bochum
Context triple: [Witten, locatedNear, Bochum]
  • A. Bochum chosen
    Bochum is a major city in Germany’s Ruhr region known for its industrial heritage, cultural institutions, and large university.
  • B. Gelsenkirchen
    Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
  • C. Krefeld
    Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
  • D. Recklinghausen
    Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
  • E. Mülheim an der Ruhr
    Mülheim an der Ruhr is a city in western Germany’s Ruhr area, known for its industrial heritage, riverside setting on the Ruhr River, and role as a regional economic and cultural center.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f6d34c8190ba19dc2df7d42c22 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fda9009ce88190b77c8f02f38107e1 completed May 8, 2026, 9:12 a.m.
Created at: April 9, 2026, 9:29 p.m.