Triple

T10209013
Position Surface form Disambiguated ID Type / Status
Subject Siemens Healthineers E242278 entity
Predicate headquartersLocation P62 FINISHED
Object Erlangen, Germany E80092 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: Erlangen, Germany | Statement: [Siemens Healthineers, headquartersLocation, Erlangen, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erlangen, Germany
Context triple: [Siemens Healthineers, headquartersLocation, Erlangen, Germany]
  • A. Giessen, Germany
    Giessen, Germany is a central German university town in the state of Hesse, known for its large student population and academic institutions.
  • B. Schröttinghausen, Germany
    Schröttinghausen is a small locality in Germany best known as the birthplace of influential astronomer Walter Baade.
  • C. Würzburg, Germany
    Würzburg, Germany is a historic city in northern Bavaria known for its baroque and rococo architecture, prominent university, and renowned Franconian wine culture.
  • D. Erlangen chosen
    Erlangen is a city in northern Bavaria, Germany, known for its university, research institutions, and historical association with mathematician Emmy Noether.
  • E. Brühl, Germany
    Brühl, Germany is a town in North Rhine-Westphalia known for its UNESCO-listed Augustusburg and Falkenlust palaces and its proximity to Cologne.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d395fa86cc8190b4f115b5a0f99772 completed April 6, 2026, 11:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d652cca9c081909f705365c70db009 completed April 8, 2026, 1:06 p.m.
Created at: April 6, 2026, 10:59 a.m.