Triple

T32914770
Position Surface form Disambiguated ID Type / Status
Subject Johann Georg Göschen E841974 entity
Predicate employer P7 FINISHED
Object Göschen publishing house
Göschen publishing house was a prominent German publishing firm founded by Johann Georg Göschen, known for issuing influential literary and scholarly works in the late 18th and early 19th centuries.
E2027359 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: Göschen publishing house | Statement: [Johann Georg Göschen, employer, Göschen publishing house]
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: Göschen publishing house
Triple: [Johann Georg Göschen, employer, Göschen publishing house]
Generated description
Göschen publishing house was a prominent German publishing firm founded by Johann Georg Göschen, known for issuing influential literary and scholarly works in the late 18th and early 19th centuries.

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_69f3494779388190a5d3e97f92278be2 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d0a19808819090c6ef1cab9caa05 completed May 3, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c69ba59c81908e3b344b88c8069f completed June 19, 2026, 4:33 a.m.
NEDg Description generation batch_6a34c8099fcc8190a33a3dcf68af6e3c completed June 19, 2026, 4:39 a.m.
NED2 Entity disambiguation (via description) batch_6a34c884ca608190ac64f8cf72d50d18 completed June 19, 2026, 4:41 a.m.
Created at: May 1, 2026, 1:19 a.m.