Triple

T37944262
Position Surface form Disambiguated ID Type / Status
Subject John C. Wright E946564 entity
Predicate notableWork P4 FINISHED
Object The Judge of Ages
The Judge of Ages is a science fiction novel by John C. Wright, part of his far-future Count to the Eschaton sequence, blending space opera, grand-scale cosmology, and philosophical themes.
 E2249914 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 Judge of Ages | Statement: [John C. Wright, notableWork, The Judge of Ages]
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 Judge of Ages
Triple: [John C. Wright, notableWork, The Judge of Ages]
Generated description
The Judge of Ages is a science fiction novel by John C. Wright, part of his far-future Count to the Eschaton sequence, blending space opera, grand-scale cosmology, and philosophical themes.

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_69f76ef531ac8190ae6d99e5786e76ec completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbdb5f3588190bf98b0c231d72002 completed May 6, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4117f811508190838b713f657f1312 completed June 28, 2026, 12:47 p.m.
NEDg Description generation batch_6a4118c579d08190b3820b73a5d6ba1a completed June 28, 2026, 12:51 p.m.
NED2 Entity disambiguation (via description) batch_6a4119f543f88190bf09c8f9de2d1ca9 completed June 28, 2026, 12:56 p.m.
Created at: May 3, 2026, 4:20 p.m.