Triple

T35600941
Position Surface form Disambiguated ID Type / Status
Subject Stadtverwaltung Erlangen E1028759 entity
Predicate hasPart P35 FINISHED
Object Amt für Digitalisierung und IT Erlangen
Das Amt für Digitalisierung und IT Erlangen ist die zentrale kommunale Fachstelle der Stadt Erlangen für Informations- und Kommunikationstechnik sowie digitale Verwaltungsservices.
E2147226 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: Amt für Digitalisierung und IT Erlangen | Statement: [Stadtverwaltung Erlangen, hasPart, Amt für Digitalisierung und IT Erlangen]
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: Amt für Digitalisierung und IT Erlangen
Triple: [Stadtverwaltung Erlangen, hasPart, Amt für Digitalisierung und IT Erlangen]
Generated description
Das Amt für Digitalisierung und IT Erlangen ist die zentrale kommunale Fachstelle der Stadt Erlangen für Informations- und Kommunikationstechnik sowie digitale Verwaltungsservices.

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_69f76e0598dc8190a6a093e904b9aa70 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79ead185081908f08b3a902c885e9 completed May 3, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a385be317e08190aa64097a8d7f766d completed June 21, 2026, 9:47 p.m.
NEDg Description generation batch_6a385d4a1b9c81908f8eaca4b6fb952e completed June 21, 2026, 9:53 p.m.
NED2 Entity disambiguation (via description) batch_6a385dd6f1808190ab7f9530743cf1d6 completed June 21, 2026, 9:55 p.m.
Created at: May 3, 2026, 4:05 p.m.