Triple

T14470728
Position Surface form Disambiguated ID Type / Status
Subject Johann Heinrich von Thünen Institute facilities E358832 entity
Predicate affiliation P10 FINISHED
Object German federal research institutions network
The German federal research institutions network is a coordinated system of government-funded scientific organizations in Germany that conduct applied and policy-relevant research across diverse fields to support national decision-making and innovation.
E1101298 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: German federal research institutions network | Statement: [Johann Heinrich von Thünen Institute facilities, affiliation, German federal research institutions network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: German federal research institutions network
Context triple: [Johann Heinrich von Thünen Institute facilities, affiliation, German federal research institutions network]
  • A. Berlin-Brandenburg research networks
    Berlin-Brandenburg research networks are collaborative scientific alliances in the Berlin-Brandenburg region that connect universities, research institutes, and other partners to advance interdisciplinary research and innovation.
  • B. Helmholtz Association
    The Helmholtz Association is Germany’s largest scientific research organization, operating a network of national research centers that conduct long-term, large-scale research in areas such as energy, health, environment, and technology.
  • C. German astronomical research network
    The German astronomical research network is a collaborative national framework that coordinates and supports astronomy and astrophysics research across multiple observatories and institutes in Germany.
  • D. German Research Foundation
    The German Research Foundation is Germany’s central self-governing research funding organization, supporting research projects and infrastructure across all disciplines at universities and research institutions.
  • E. German Universities of Technology network
    The German Universities of Technology network is an alliance of leading German technical universities that collaborate on research, teaching, and innovation in engineering and the applied sciences.
  • 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: German federal research institutions network
Triple: [Johann Heinrich von Thünen Institute facilities, affiliation, German federal research institutions network]
Generated description
The German federal research institutions network is a coordinated system of government-funded scientific organizations in Germany that conduct applied and policy-relevant research across diverse fields to support national decision-making and innovation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: German federal research institutions network
Target entity description: The German federal research institutions network is a coordinated system of government-funded scientific organizations in Germany that conduct applied and policy-relevant research across diverse fields to support national decision-making and innovation.
  • A. Berlin-Brandenburg research networks
    Berlin-Brandenburg research networks are collaborative scientific alliances in the Berlin-Brandenburg region that connect universities, research institutes, and other partners to advance interdisciplinary research and innovation.
  • B. Helmholtz Association
    The Helmholtz Association is Germany’s largest scientific research organization, operating a network of national research centers that conduct long-term, large-scale research in areas such as energy, health, environment, and technology.
  • C. German astronomical research network
    The German astronomical research network is a collaborative national framework that coordinates and supports astronomy and astrophysics research across multiple observatories and institutes in Germany.
  • D. German Research Foundation
    The German Research Foundation is Germany’s central self-governing research funding organization, supporting research projects and infrastructure across all disciplines at universities and research institutions.
  • E. German Universities of Technology network
    The German Universities of Technology network is an alliance of leading German technical universities that collaborate on research, teaching, and innovation in engineering and the applied sciences.
  • 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_69d827966698819082e140837737501d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91f969788190a5114f92d7159aae completed April 14, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd649beec88190861abb52c5a2733e completed May 8, 2026, 4:20 a.m.
NEDg Description generation batch_69fd67b1ed2081908d3de6514078be49 completed May 8, 2026, 4:33 a.m.
NED2 Entity disambiguation (via description) batch_69fd682f28948190adc037c18c7deb93 completed May 8, 2026, 4:35 a.m.
Created at: April 10, 2026, 1:20 a.m.