Triple

T34382746
Position Surface form Disambiguated ID Type / Status
Subject Creating a World Without Poverty E882480 entity
Predicate author P4 FINISHED
Object Karl Weber
Karl Weber is an American writer and editor known for collaborating on and adapting influential works on social entrepreneurship, economics, and public policy.
E2187483 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: Karl Weber | Statement: [Creating a World Without Poverty, author, Karl Weber]
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: Karl Weber
Triple: [Creating a World Without Poverty, author, Karl Weber]
Generated description
Karl Weber is an American writer and editor known for collaborating on and adapting influential works on social entrepreneurship, economics, and public policy.

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_69f349c0219881909393bbbc1edc8161 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f718730fc88190b06cdfff882081b7 completed May 3, 2026, 9:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a39dbb0e9388190a5f7cef4ca7d8d3a completed June 23, 2026, 1:04 a.m.
NEDg Description generation batch_6a39dfec48e08190b42db43d49767409 completed June 23, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a39e055f3988190a10d812e50672758 completed June 23, 2026, 1:24 a.m.
Created at: May 1, 2026, 1:59 a.m.