Triple

T27346934
Position Surface form Disambiguated ID Type / Status
Subject Lonely Runs Both Ways E684255 entity
Predicate hasPart P35 FINISHED
Object A Living Prayer
"A Living Prayer" is a country-gospel ballad by Alison Krauss & Union Station, noted for its spiritual lyrics and Krauss's ethereal vocal performance.
 E1767821 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: A Living Prayer | Statement: [Lonely Runs Both Ways, hasPart, A Living Prayer]
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: A Living Prayer
Triple: [Lonely Runs Both Ways, hasPart, A Living Prayer]
Generated description
"A Living Prayer" is a country-gospel ballad by Alison Krauss & Union Station, noted for its spiritual lyrics and Krauss's ethereal vocal performance.

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_69ef1480a76481908684256ddd5bfda3 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62ba48564819091f2f7f2db3178ce completed May 2, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129ccb46588190b076fc5c8475879b completed May 24, 2026, 6:38 a.m.
NEDg Description generation batch_6a129dc563e081909b6e07e29aad6ddb completed May 24, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_6a129e5f7e348190af4a279de8ef8caa completed May 24, 2026, 6:44 a.m.
Created at: April 27, 2026, 11:46 a.m.