Triple

T34848937
Position Surface form Disambiguated ID Type / Status
Subject Ulrike Meinhof E1004547 entity
Predicate employer P7 FINISHED
Object Konkret
Konkret was a prominent left-wing German political magazine known for its critical, radical journalism during the postwar and 1960s era.
E2115571 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: Konkret | Statement: [Ulrike Meinhof, employer, Konkret]
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: Konkret
Triple: [Ulrike Meinhof, employer, Konkret]
Generated description
Konkret was a prominent left-wing German political magazine known for its critical, radical journalism during the postwar and 1960s era.

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_69f76dba76f0819090643cba102c41ec completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78138fc0081908ae6f7e73c54e950 completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37795449d48190b3b7b79308d2e59e completed June 21, 2026, 5:40 a.m.
NEDg Description generation batch_6a377a96309c819083da53a3ce65dbd6 completed June 21, 2026, 5:45 a.m.
NED2 Entity disambiguation (via description) batch_6a377b79f9c08190bb5125de50e0ad2a completed June 21, 2026, 5:49 a.m.
Created at: May 3, 2026, 4 p.m.