Triple

T24838522
Position Surface form Disambiguated ID Type / Status
Subject Hanns Martin Schleyer E621545 entity
Predicate memberOf P10 FINISHED
Object Federation of German Industries
The Federation of German Industries is a leading umbrella organization representing the interests of Germany’s industrial and business sectors at the national and international levels.
E1655317 NE FINISHED

How this triple was built (2 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: Federation of German Industries | Statement: [Hanns Martin Schleyer, memberOf, Federation of German Industries]
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: Federation of German Industries
Triple: [Hanns Martin Schleyer, memberOf, Federation of German Industries]
Generated description
The Federation of German Industries is a leading umbrella organization representing the interests of Germany’s industrial and business sectors at the national and international levels.

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_69e2fac185d48190a0a6073ad1f6b792 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422b94d348190a77e31166a24c921 completed May 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10331666dc8190b9231fafe98e0f32 completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a1033999eb8819093313456a2a6fb1b completed May 22, 2026, 10:44 a.m.
NED2 Entity disambiguation (via description) batch_6a10344ac26c81908a031f43caf710b5 completed May 22, 2026, 10:47 a.m.
Created at: April 18, 2026, 5:18 a.m.