Triple

T28752576
Position Surface form Disambiguated ID Type / Status
Subject Malcolm E731571 entity
Predicate hasMainCharacter P1183 FINISHED
Object Malcolm Hughes
Malcolm Hughes is a fictional character named Malcolm who serves as the main protagonist in the work in which he appears.
E1853274 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: Malcolm Hughes | Statement: [Malcolm, hasMainCharacter, Malcolm Hughes]
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: Malcolm Hughes
Triple: [Malcolm, hasMainCharacter, Malcolm Hughes]
Generated description
Malcolm Hughes is a fictional character named Malcolm who serves as the main protagonist in the work in which he appears.

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_69f043ed68a881909e858a06bab7a247 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f657f850d481908594b61ec457b2ff completed May 2, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_6a255037dd4481908a1cfead8d22470b completed June 7, 2026, 11:04 a.m.
NEDg Description generation batch_6a25547c1cb881909b0a85b2bb6d61f1 completed June 7, 2026, 11:22 a.m.
NED2 Entity disambiguation (via description) batch_6a2558d26f808190b01d391c806b780d completed June 7, 2026, 11:41 a.m.
Created at: April 28, 2026, 6:08 a.m.