Triple

T14497057
Position Surface form Disambiguated ID Type / Status
Subject M. Paul Friedberg E359527 entity
Predicate familyName P18 FINISHED
Object Friedberg
Friedberg is a German-origin surname borne by various notable individuals across fields such as landscape architecture, academia, and the arts.
E1103242 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: Friedberg | Statement: [M. Paul Friedberg, familyName, Friedberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friedberg
Context triple: [M. Paul Friedberg, familyName, Friedberg]
  • A. Friedberg
    Friedberg is a historic German town in the state of Hesse, known for its medieval fortifications and strategic importance during the Seven Years' War.
  • B. Kleinfeld
    Kleinfeld is a corrupt, cocaine-addicted lawyer in the crime film "Carlito's Way," whose reckless actions help drive the story’s tragic downfall.
  • C. Guttstadt
    Guttstadt is the former German name of the town now known as Dobre Miasto in northern Poland.
  • D. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • E. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • 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: Friedberg
Triple: [M. Paul Friedberg, familyName, Friedberg]
Generated description
Friedberg is a German-origin surname borne by various notable individuals across fields such as landscape architecture, academia, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Friedberg
Target entity description: Friedberg is a German-origin surname borne by various notable individuals across fields such as landscape architecture, academia, and the arts.
  • A. Friedberg
    Friedberg is a historic German town in the state of Hesse, known for its medieval fortifications and strategic importance during the Seven Years' War.
  • B. Kleinfeld
    Kleinfeld is a corrupt, cocaine-addicted lawyer in the crime film "Carlito's Way," whose reckless actions help drive the story’s tragic downfall.
  • C. Guttstadt
    Guttstadt is the former German name of the town now known as Dobre Miasto in northern Poland.
  • D. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • E. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de93109cb081909a6e846db23a4635 completed April 14, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d9731588190b27a826582e5fc6d completed May 8, 2026, 4:59 a.m.
NEDg Description generation batch_69fd6f82453481909a3e1b032f30a7a5 completed May 8, 2026, 5:07 a.m.
NED2 Entity disambiguation (via description) batch_69fd708521c881909863b7cd3fc4a313 completed May 8, 2026, 5:11 a.m.
Created at: April 10, 2026, 1:21 a.m.