Triple

T32815294
Position Surface form Disambiguated ID Type / Status
Subject Hochschule für Gestaltung Schwäbisch Gmünd E839270 entity
Predicate offersProgram P178 FINISHED
Object Master in Strategic Design
The Master in Strategic Design is a graduate program focused on integrating design thinking, strategy, and innovation to address complex social, technological, and business challenges.
E2022405 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: Master in Strategic Design | Statement: [Hochschule für Gestaltung Schwäbisch Gmünd, offersProgram, Master in Strategic Design]
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: Master in Strategic Design
Triple: [Hochschule für Gestaltung Schwäbisch Gmünd, offersProgram, Master in Strategic Design]
Generated description
The Master in Strategic Design is a graduate program focused on integrating design thinking, strategy, and innovation to address complex social, technological, and business challenges.

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_69f3493df9008190a8f5d843dcd77704 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cdce62d4819082dc7ea3214764e4 completed May 3, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b17e286c819085bcd7e122099f94 completed June 19, 2026, 3:03 a.m.
NEDg Description generation batch_6a34b20e8e9881909b3a425431f5a449 completed June 19, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a34b28efeac819080bec50507fcb9c4 completed June 19, 2026, 3:07 a.m.
Created at: May 1, 2026, 1:15 a.m.