Triple

T30098619
Position Surface form Disambiguated ID Type / Status
Subject Sir Percival E764933 entity
Predicate notableFor P22 FINISHED
Object Arthurian romance
Arthurian romance is a medieval literary genre of chivalric tales centered on King Arthur, his knights, and their quests, blending adventure, courtly love, and the supernatural.
E67105 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: Arthurian romance | Statement: [Sir Percival, notableFor, Arthurian romance]
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: Arthurian romance
Triple: [Sir Percival, notableFor, Arthurian romance]
Generated description
Arthurian romance is a medieval literary genre of chivalric tales centered on King Arthur, his knights, and their quests, blending adventure, courtly love, and the supernatural.

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_69f22474e4288190b5f895fe3974aa92 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67d92dbdc8190ae3e8f67b979cb5c completed May 2, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a277bfb2aa48190a4901d811532e941 completed June 9, 2026, 2:35 a.m.
NEDg Description generation batch_6a277cab7a848190b3bb869bb2f794fa completed June 9, 2026, 2:38 a.m.
NED2 Entity disambiguation (via description) batch_6a277d7238a481909b4eccfff1d10aa9 completed June 9, 2026, 2:41 a.m.
Created at: April 29, 2026, 7:08 p.m.