Triple

T2687677
Position Surface form Disambiguated ID Type / Status
Subject Grand Duchy of Berg E57522 entity
Predicate namedAfter P63 FINISHED
Object Berg
Berg was a historical German territorial entity that gave its name to the later Grand Duchy of Berg in the Rhineland region.
 E287565 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: Berg | Statement: [Grand Duchy of Berg, namedAfter, Berg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Berg
Context triple: [Grand Duchy of Berg, namedAfter, Berg]
  • A. Wilseder Berg
    Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
  • B. Hoche
    Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
  • C. Gora
    Gora is a major Bengali novel by Rabindranath Tagore that explores themes of identity, nationalism, and religious and social reform in colonial India.
  • D. Alsberg
    Alsberg is a surname of Germanic origin borne by various notable individuals, including American writer and theater director Henry Alsberg.
  • E. Brocken
    Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
  • 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: Berg
Triple: [Grand Duchy of Berg, namedAfter, Berg]
Generated description
Berg was a historical German territorial entity that gave its name to the later Grand Duchy of Berg in the Rhineland region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Berg
Target entity description: Berg was a historical German territorial entity that gave its name to the later Grand Duchy of Berg in the Rhineland region.
  • A. Wilseder Berg
    Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
  • B. Hoche
    Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
  • C. Gora
    Gora is a major Bengali novel by Rabindranath Tagore that explores themes of identity, nationalism, and religious and social reform in colonial India.
  • D. Alsberg
    Alsberg is a surname of Germanic origin borne by various notable individuals, including American writer and theater director Henry Alsberg.
  • E. Brocken
    Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9f1ba3081909a349a2f30f8f9c9 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa0741bc48190adffe6cfae831e26 completed March 10, 2026, 4:39 a.m.
NEDg Description generation batch_69afa13a81bc819091463e6589e72361 completed March 10, 2026, 4:42 a.m.
NED2 Entity disambiguation (via description) batch_69afa1ab8da8819090af3ed60b417040 completed March 10, 2026, 4:44 a.m.
Created at: March 6, 2026, 9:54 p.m.