Triple

T26753295

Position	Surface form	Disambiguated ID	Type / Status
Subject	ceremonial county of Rutland	`E674599`	entity
Predicate	hasMotto	`P42`	FINISHED
Object	Multum in Parvo Multum in Parvo is the Latin motto of the English ceremonial county of Rutland, meaning “much in little” and reflecting its small size yet rich character.	`E1737702`	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: Multum in Parvo | Statement: [ceremonial county of Rutland, hasMotto, Multum in Parvo]

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: Multum in Parvo
Triple: [ceremonial county of Rutland, hasMotto, Multum in Parvo]

Generated description

Multum in Parvo is the Latin motto of the English ceremonial county of Rutland, meaning “much in little” and reflecting its small size yet rich character.

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_69eecda6e9dc81908452fab3ba17ed9b`	completed	April 27, 2026, 2:44 a.m.
NER	Named-entity recognition	`batch_69f618cea64c819087537ce89b2fec9c`	completed	May 2, 2026, 3:31 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a11feb06b5081908da123a5fb34832f`	completed	May 23, 2026, 7:23 p.m.
NEDg	Description generation	`batch_6a11ff2e71988190ad6d34bc5420c9bd`	completed	May 23, 2026, 7:25 p.m.
NED2	Entity disambiguation (via description)	`batch_6a11ffe6aad4819096be2e81c2f3d1b0`	completed	May 23, 2026, 7:28 p.m.

Created at: April 27, 2026, 3:54 a.m.