Triple

T34089292
Position Surface form Disambiguated ID Type / Status
Subject Sons of Encouragement series E874259 entity
Predicate hasPart P35 FINISHED
Object The Prince
The Prince is a historical Christian novel by Francine Rivers that focuses on the biblical figure Jonathan, exploring his faith, loyalty, and relationship with David.
E2081089 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: The Prince | Statement: [Sons of Encouragement series, hasPart, The Prince]
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: The Prince
Triple: [Sons of Encouragement series, hasPart, The Prince]
Generated description
The Prince is a historical Christian novel by Francine Rivers that focuses on the biblical figure Jonathan, exploring his faith, loyalty, and relationship with David.

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_69f349a61d448190b74642f325d3eb7a completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70c1148bc8190a5db30814851b041 completed May 3, 2026, 8:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36ae5a2c98819097a40cf0eb061b75 completed June 20, 2026, 3:14 p.m.
NEDg Description generation batch_6a36af3eb7288190bee994ee99c9cb56 completed June 20, 2026, 3:18 p.m.
NED2 Entity disambiguation (via description) batch_6a36afe7a9208190952f11924f15856b completed June 20, 2026, 3:21 p.m.
Created at: May 1, 2026, 1:52 a.m.