Triple

T28521083
Position Surface form Disambiguated ID Type / Status
Subject Richie Grenadine E721767 entity
Predicate fictionalUniverse P3758 FINISHED
Object Gray Matter universe
The Gray Matter universe is a fictional setting that serves as the narrative world for stories featuring the character Richie Grenadine.
E1823633 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: Gray Matter universe | Statement: [Richie Grenadine, fictionalUniverse, Gray Matter universe]
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: Gray Matter universe
Triple: [Richie Grenadine, fictionalUniverse, Gray Matter universe]
Generated description
The Gray Matter universe is a fictional setting that serves as the narrative world for stories featuring the character Richie Grenadine.

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_69f01a5cbcc4819083fb4e723378713e completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f64fa24a6481908c8b6651cbaf0664 completed May 2, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac58c64c8190a7c9a8a31578f87a completed May 31, 2026, 9:47 p.m.
NEDg Description generation batch_6a1cad2074c88190b059e7a591857302 completed May 31, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a1cb1010f94819092380c7428bfac26 completed May 31, 2026, 10:06 p.m.
Created at: April 28, 2026, 3:20 a.m.