Triple

T28551368
Position Surface form Disambiguated ID Type / Status
Subject Austrian press E722892 entity
Predicate hasMajorNewspaper P15739 FINISHED
Object Salzburger Nachrichten
Salzburger Nachrichten is a leading Austrian daily newspaper based in Salzburg, known for its comprehensive national and regional news coverage and liberal-conservative editorial stance.
E1822986 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: Salzburger Nachrichten | Statement: [Austrian press, hasMajorNewspaper, Salzburger Nachrichten]
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: Salzburger Nachrichten
Triple: [Austrian press, hasMajorNewspaper, Salzburger Nachrichten]
Generated description
Salzburger Nachrichten is a leading Austrian daily newspaper based in Salzburg, known for its comprehensive national and regional news coverage and liberal-conservative editorial stance.

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_69f01a60204481909af1bb76247b8221 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69fed535dd2081908d52cac08201fc57 completed May 9, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac6fa49c8190a70635026c4c34ba completed May 31, 2026, 9:47 p.m.
NEDg Description generation batch_6a1cade75d608190a1306aa6f0652f68 completed May 31, 2026, 9:53 p.m.
NED2 Entity disambiguation (via description) batch_6a1cae5c32f081908777415e8e460ee5 completed May 31, 2026, 9:55 p.m.
Created at: April 28, 2026, 3:42 a.m.