Triple

T36700300
Position Surface form Disambiguated ID Type / Status
Subject Mauricius E906207 entity
Predicate hasCognate P2525 FINISHED
Object Morris
Morris is a masculine given name, historically used in English-speaking countries and often associated with variants like Maurice or Mauricius.
E1291670 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: Morris | Statement: [Mauricius, hasCognate, Morris]
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: Morris
Triple: [Mauricius, hasCognate, Morris]
Generated description
Morris is a masculine given name, historically used in English-speaking countries and often associated with variants like Maurice or Mauricius.

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_69f76e7195c48190b5580c9cfb01e95f completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c7ec9f50819094e17f67f19f8f2c completed May 3, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3c172439988190ae0c57a03f60c1ea completed June 24, 2026, 5:43 p.m.
NEDg Description generation batch_6a3c17bef5988190bf7bbafbaaeebef1 completed June 24, 2026, 5:45 p.m.
NED2 Entity disambiguation (via description) batch_6a3c6c139c748190befd6b09cf6171b2 completed June 24, 2026, 11:45 p.m.
Created at: May 3, 2026, 4:12 p.m.