Triple

T24651680
Position Surface form Disambiguated ID Type / Status
Subject Federal Agency for Technical Relief E610265 entity
Predicate youthOrganizationName P50178 FINISHED
Object THW-Jugend
THW-Jugend is the youth organization of Germany’s Federal Agency for Technical Relief, where young people are introduced to volunteer civil protection and technical assistance work.
 E1645756 NE FINISHED

How this triple was built (3 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: THW-Jugend | Statement: [Federal Agency for Technical Relief, youthOrganizationName, THW-Jugend]
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: THW-Jugend
Triple: [Federal Agency for Technical Relief, youthOrganizationName, THW-Jugend]
Generated description
THW-Jugend is the youth organization of Germany’s Federal Agency for Technical Relief, where young people are introduced to volunteer civil protection and technical assistance work.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: youthOrganizationName
Context triple: [Federal Agency for Technical Relief, youthOrganizationName, THW-Jugend]
  • A. youthWingName chosen
    Indicates the name assigned to the youth wing or youth branch associated with an organization, group, or party.
  • B. youthWingAbbreviation
    Indicates the abbreviated name used to refer to a political party’s youth wing.
  • C. hasStudentOrganization
    Indicates that an entity (such as an institution or department) is associated with or hosts a particular student organization.
  • D. hasYouthProgram
    Indicates that an entity offers or is associated with an organized program or set of activities specifically designed for young people.
  • E. youthLeader
    Indicates that an entity holds a leadership role within a youth-focused group, organization, or activity.
  • F. None of above.

Provenance (6 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_69e2c4d350a481909170482bc2ce6af9 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f41011d8048190be70329ba0bfb7c7 completed May 1, 2026, 2:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10049ac3a481909fc8eae6b8f9cdf8 completed May 22, 2026, 7:24 a.m.
NEDg Description generation batch_6a10095d986881909082cc5a32b6d56e completed May 22, 2026, 7:44 a.m.
NED2 Entity disambiguation (via description) batch_6a1009d311b08190acf35a3ed552b9c1 completed May 22, 2026, 7:46 a.m.
PD Predicate disambiguation batch_69f40ed9d47881909fcfc0d04e8d074a completed May 1, 2026, 2:24 a.m.
Created at: April 18, 2026, 2:34 a.m.