Triple

T30139180
Position Surface form Disambiguated ID Type / Status
Subject Lionel E766078 entity
Predicate relatedWork P37 FINISHED
Object Lancelot-Grail
Lancelot-Grail is a major 13th-century French prose cycle of Arthurian romances that centers on Lancelot and the quest for the Holy Grail.
E1913974 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: Lancelot-Grail | Statement: [Lionel, relatedWork, Lancelot-Grail]
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: Lancelot-Grail
Triple: [Lionel, relatedWork, Lancelot-Grail]
Generated description
Lancelot-Grail is a major 13th-century French prose cycle of Arthurian romances that centers on Lancelot and the quest for the Holy Grail.

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_69f2247909048190ae86c2160cf8b566 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67e86d38c8190a100b82da345b6ca completed May 2, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a278923f27881909506585b590a1865 completed June 9, 2026, 3:31 a.m.
NEDg Description generation batch_6a2791be55188190b525ac6b93e0f2ff completed June 9, 2026, 4:08 a.m.
NED2 Entity disambiguation (via description) batch_6a27926b70f88190ab70a69f6619e8f7 completed June 9, 2026, 4:11 a.m.
Created at: April 29, 2026, 7:17 p.m.