Triple

T27234525
Position Surface form Disambiguated ID Type / Status
Subject Nestor E682238 entity
Predicate fictionalUniverse P3758 FINISHED
Object Tintin universe
The Tintin universe is the fictional world of Hergé’s comic series, featuring the adventures of young reporter Tintin, his dog Snowy, and a recurring cast of characters across globe-trotting mysteries.
E1765798 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: Tintin universe | Statement: [Nestor, fictionalUniverse, Tintin 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: Tintin universe
Triple: [Nestor, fictionalUniverse, Tintin universe]
Generated description
The Tintin universe is the fictional world of Hergé’s comic series, featuring the adventures of young reporter Tintin, his dog Snowy, and a recurring cast of characters across globe-trotting mysteries.

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_69eefacdad7881908b7bca61c90a1a1e completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f626784b188190aaafe6e8123a12b9 completed May 2, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129c999bc08190879e1d42d442f82b completed May 24, 2026, 6:37 a.m.
NEDg Description generation batch_6a129e0722388190bce1a8749df3f7bf completed May 24, 2026, 6:43 a.m.
NED2 Entity disambiguation (via description) batch_6a129e7b3f508190b7cc7b6f40177927 completed May 24, 2026, 6:45 a.m.
Created at: April 27, 2026, 9:47 a.m.