Triple

T25176187
Position Surface form Disambiguated ID Type / Status
Subject Tulla Pokriefke E630452 entity
Predicate hasChild P369 FINISHED
Object Paul Pokriefke
Paul Pokriefke is a fictional German journalist and narrator in Günter Grass’s novel "Crabwalk," whose life is deeply shaped by the legacy of World War II and his mother Tulla’s traumatic past.
E621540 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: Paul Pokriefke | Statement: [Tulla Pokriefke, hasChild, Paul Pokriefke]
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: Paul Pokriefke
Triple: [Tulla Pokriefke, hasChild, Paul Pokriefke]
Generated description
Paul Pokriefke is a fictional German journalist and narrator in Günter Grass’s novel "Crabwalk," whose life is deeply shaped by the legacy of World War II and his mother Tulla’s traumatic past.

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_69e75a88fdf081908e47ae6e195c14e1 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46dc040088190958bb7a6633fd016 completed May 1, 2026, 9:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067c8430c8190b3d8046c265c9800 completed May 22, 2026, 2:27 p.m.
NEDg Description generation batch_6a10695d0e648190b51f82934d5f2800 completed May 22, 2026, 2:34 p.m.
NED2 Entity disambiguation (via description) batch_6a1069d0ba8c81908b38818567784552 completed May 22, 2026, 2:36 p.m.
Created at: April 21, 2026, 12:34 p.m.