Triple

T13913789
Position Surface form Disambiguated ID Type / Status
Subject Technische Nothilfe E334564 entity
Predicate shortName P43 FINISHED
Object TeNo
TeNo was the abbreviated name for Technische Nothilfe, a German technical emergency relief organization active primarily during the early to mid-20th century.
 E1069040 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: TeNo | Statement: [Technische Nothilfe, shortName, TeNo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TeNo
Context triple: [Technische Nothilfe, shortName, TeNo]
  • A. Toyen
    Toyen was a Czech avant-garde painter and illustrator known for her distinctive contributions to surrealism and erotic art in 20th-century Europe.
  • B. La To
    La To is a Vietnamese deity venerated as a patron of medicine and physicians.
  • C. Todee
    Todee is a district-level administrative area located within Montserrado County in Liberia.
  • D. Teni
    Teni is a Nigerian singer-songwriter and entertainer known for her catchy Afropop hits and playful, charismatic style.
  • E. Tuyo
    "Tuyo" is a bolero-style song by Rodrigo Amarante, best known as the haunting opening theme of the television series *Narcos*.
  • 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: TeNo
Triple: [Technische Nothilfe, shortName, TeNo]
Generated description
TeNo was the abbreviated name for Technische Nothilfe, a German technical emergency relief organization active primarily during the early to mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TeNo
Target entity description: TeNo was the abbreviated name for Technische Nothilfe, a German technical emergency relief organization active primarily during the early to mid-20th century.
  • A. Toyen
    Toyen was a Czech avant-garde painter and illustrator known for her distinctive contributions to surrealism and erotic art in 20th-century Europe.
  • B. La To
    La To is a Vietnamese deity venerated as a patron of medicine and physicians.
  • C. Todee
    Todee is a district-level administrative area located within Montserrado County in Liberia.
  • D. Teni
    Teni is a Nigerian singer-songwriter and entertainer known for her catchy Afropop hits and playful, charismatic style.
  • E. Tuyo
    "Tuyo" is a bolero-style song by Rodrigo Amarante, best known as the haunting opening theme of the television series *Narcos*.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de27245c648190b2946845ce0fdbf8 completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c72a345481908f8552bca7bb1a5a completed May 3, 2026, 10:07 p.m.
NEDg Description generation batch_69f7c8d477f881908f8cfd2783e7f10f completed May 3, 2026, 10:14 p.m.
NED2 Entity disambiguation (via description) batch_69f7ca27ffd4819080bccd6bfd88ddb3 completed May 3, 2026, 10:20 p.m.
Created at: April 9, 2026, 10:16 p.m.