Triple

T34969653
Position Surface form Disambiguated ID Type / Status
Subject Legends: The Enchanted E1008499 entity
Predicate creator P184 FINISHED
Object Nick Percival
Nick Percival is a British comic book artist and writer known for his dark, painterly style on titles such as Legends: The Enchanted and various works for major publishers like Marvel and 2000 AD.
E2122678 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: Nick Percival | Statement: [Legends: The Enchanted, creator, Nick Percival]
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: Nick Percival
Triple: [Legends: The Enchanted, creator, Nick Percival]
Generated description
Nick Percival is a British comic book artist and writer known for his dark, painterly style on titles such as Legends: The Enchanted and various works for major publishers like Marvel and 2000 AD.

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_69f76dc78a308190a1ac29ad4a9a4895 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78460a2e881908064c72b49d56bba completed May 3, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37bd0c8f708190a3f59098003f0550 completed June 21, 2026, 10:29 a.m.
NEDg Description generation batch_6a37bda6c4408190a6f09442687dae28 completed June 21, 2026, 10:32 a.m.
NED2 Entity disambiguation (via description) batch_6a37bf374b7081908687f2997935411e completed June 21, 2026, 10:38 a.m.
Created at: May 3, 2026, 4 p.m.