Triple

T18057790
Position Surface form Disambiguated ID Type / Status
Subject Frida Uhl E432083 entity
Predicate familyName P18 FINISHED
Object Uhl
Uhl is a German-language surname borne by various notable individuals in fields such as the arts, sports, and academia.
E1304273 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: Uhl | Statement: [Frida Uhl, familyName, Uhl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uhl
Context triple: [Frida Uhl, familyName, Uhl]
  • A. Ulmiz
    Ulmiz is a small municipality in the canton of Fribourg in western Switzerland.
  • B. Uherka
    Uherka is a river in eastern Poland that serves as a tributary of the Western Bug, flowing through the Lublin region.
  • C. Kummerow
    Kummerow is a small municipality in northeastern Germany, known for its scenic setting on the shores of Lake Kummerow in Mecklenburg-Vorpommern.
  • D. Ulrichen
    Ulrichen is a small alpine village in the Swiss canton of Valais, known for its scenic mountain landscape and outdoor recreation opportunities.
  • E. Zamberk
    Zamberk is a small historic town in the Pardubice Region of the Czech Republic, known for its traditional architecture and scenic setting in the Orlické Mountains foothills.
  • 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: Uhl
Triple: [Frida Uhl, familyName, Uhl]
Generated description
Uhl is a German-language surname borne by various notable individuals in fields such as the arts, sports, and academia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Uhl
Target entity description: Uhl is a German-language surname borne by various notable individuals in fields such as the arts, sports, and academia.
  • A. Ulmiz
    Ulmiz is a small municipality in the canton of Fribourg in western Switzerland.
  • B. Uherka
    Uherka is a river in eastern Poland that serves as a tributary of the Western Bug, flowing through the Lublin region.
  • C. Kummerow
    Kummerow is a small municipality in northeastern Germany, known for its scenic setting on the shores of Lake Kummerow in Mecklenburg-Vorpommern.
  • D. Ulrichen
    Ulrichen is a small alpine village in the Swiss canton of Valais, known for its scenic mountain landscape and outdoor recreation opportunities.
  • E. Zamberk
    Zamberk is a small historic town in the Pardubice Region of the Czech Republic, known for its traditional architecture and scenic setting in the Orlické Mountains foothills.
  • 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4c103cedc819086a905269b118795 completed April 19, 2026, 11:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a03566907988190aef2b0ceb2c9f4dc completed May 12, 2026, 4:33 p.m.
NEDg Description generation batch_6a03591fa4cc819084d1e50b7e5263cf completed May 12, 2026, 4:45 p.m.
NED2 Entity disambiguation (via description) batch_6a0359a3ead48190996d95ad5aaa2302 completed May 12, 2026, 4:47 p.m.
Created at: April 10, 2026, 10:26 a.m.