Triple

T9971774
Position Surface form Disambiguated ID Type / Status
Subject Bernhardt E196223 entity
Predicate hasComponent P35 FINISHED
Object bern
Bern is the de facto capital city of Switzerland, known for its well-preserved medieval old town and status as the country's political center.
 E832245 NE FINISHED

How this triple was built (4 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: bern | Statement: [Bernhardt, hasComponent, bern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: bern
Context triple: [Bernhardt, hasComponent, bern]
  • A. Ber
    Ber is a traditional Yiddish given name, often associated with Ashkenazi Jewish men and sometimes used as a counterpart to the Hebrew name Dov.
  • B. BER
    BER is a U.S. Department of Energy research program that advances fundamental science on biological systems and environmental processes to address energy and climate challenges.
  • C. BER
    BER is Berlin Brandenburg Airport, the main international airport serving Germany’s capital region.
  • D. BER
    BER is the ICAO airline designator formerly used by the now-defunct German carrier Air Berlin.
  • E. Brun
    Brun is a given name and surname of Germanic origin, closely related to and often used as a variant of Bruno.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: bern
Triple: [Bernhardt, hasComponent, bern]
Generated description
Bern is the de facto capital city of Switzerland, known for its well-preserved medieval old town and status as the country's political center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: bern
Target entity description: Bern is the de facto capital city of Switzerland, known for its well-preserved medieval old town and status as the country's political center.
  • A. Ber
    Ber is a traditional Yiddish given name, often associated with Ashkenazi Jewish men and sometimes used as a counterpart to the Hebrew name Dov.
  • B. BER
    BER is a U.S. Department of Energy research program that advances fundamental science on biological systems and environmental processes to address energy and climate challenges.
  • C. BER
    BER is Berlin Brandenburg Airport, the main international airport serving Germany’s capital region.
  • D. BER
    BER is the ICAO airline designator formerly used by the now-defunct German carrier Air Berlin.
  • E. Brun
    Brun is a given name and surname of Germanic origin, closely related to and often used as a variant of Bruno.
  • F. None of above. chosen

Provenance (5 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_69ca82eea2b88190a0e511d21a31f386 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb7bb03688190a3f4fc1988b8fafa completed April 2, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23dd3e47c819095fef68b9939ec19 completed April 5, 2026, 10:47 a.m.
NEDg Description generation batch_69d23eb2971c8190bcdbc31b4ef19816 completed April 5, 2026, 10:51 a.m.
NED2 Entity disambiguation (via description) batch_69d240d7b7e881909183d7c33bd8cb5b completed April 5, 2026, 11 a.m.
Created at: March 30, 2026, 8:48 p.m.