Triple

T33685183
Position Surface form Disambiguated ID Type / Status
Subject "Didn't It Rain" E863005 entity
Predicate notablePerformer P17435 FINISHED
Object Marion Williams
Marion Williams was a renowned American gospel singer celebrated for her powerful, soaring voice and influential performances that helped shape modern gospel music.
E2088793 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: Marion Williams | Statement: ["Didn't It Rain", notablePerformer, Marion Williams]
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: Marion Williams
Triple: ["Didn't It Rain", notablePerformer, Marion Williams]
Generated description
Marion Williams was a renowned American gospel singer celebrated for her powerful, soaring voice and influential performances that helped shape modern gospel music.

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_69f3498662b48190904442c39df84fb7 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fa641c608190827254fa7958f4bc completed May 3, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36e6048cbc8190998dba12a0f6019b completed June 20, 2026, 7:12 p.m.
NEDg Description generation batch_6a36e8413ddc8190b80406d6a133e849 completed June 20, 2026, 7:21 p.m.
NED2 Entity disambiguation (via description) batch_6a36e8d2a5888190b17c1bcb890c90df completed June 20, 2026, 7:24 p.m.
Created at: May 1, 2026, 1:43 a.m.