Triple

T33479322
Position Surface form Disambiguated ID Type / Status
Subject Lt. Gen. George Miller E857421 entity
Predicate fictionalUniverse P3758 FINISHED
Object In the Loop universe
The In the Loop universe is the satirical political world depicted in the British film and related works, portraying chaotic government spin, diplomatic blunders, and behind-the-scenes maneuvering around a fictional Middle East war.
E2054224 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: In the Loop universe | Statement: [Lt. Gen. George Miller, fictionalUniverse, In the Loop 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: In the Loop universe
Triple: [Lt. Gen. George Miller, fictionalUniverse, In the Loop universe]
Generated description
The In the Loop universe is the satirical political world depicted in the British film and related works, portraying chaotic government spin, diplomatic blunders, and behind-the-scenes maneuvering around a fictional Middle East war.

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_69f3497472508190b300ebd3fd402367 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e52e174081908ff9fe1af15586a3 completed May 3, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3595b1a3e881908d8c304db59a75e9 completed June 19, 2026, 7:17 p.m.
NEDg Description generation batch_6a3596c81644819097f9237ed4ec071d completed June 19, 2026, 7:21 p.m.
NED2 Entity disambiguation (via description) batch_6a35978115108190894086f7f04c81cf completed June 19, 2026, 7:24 p.m.
Created at: May 1, 2026, 1:38 a.m.