Triple

T32300633

Position	Surface form	Disambiguated ID	Type / Status
Subject	Battle of Aurelianum	`E825227`	entity
Predicate	namedAfter	`P63`	FINISHED
Object	Aurelianum (Latin name of Orléans) Aurelianum is the Latin name for the historic French city of Orléans, an important center on the Loire River known for its medieval and Roman heritage.	`E2002826`	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: Aurelianum (Latin name of Orléans) | Statement: [Battle of Aurelianum, namedAfter, Aurelianum (Latin name of Orléans)]

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: Aurelianum (Latin name of Orléans)
Triple: [Battle of Aurelianum, namedAfter, Aurelianum (Latin name of Orléans)]

Generated description

Aurelianum is the Latin name for the historic French city of Orléans, an important center on the Loire River known for its medieval and Roman heritage.

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_69f349115304819084ee91d345b6c8aa`	completed	April 30, 2026, 12:20 p.m.
NER	Named-entity recognition	`batch_69f6bd7481988190addeb1c9acd75386`	completed	May 3, 2026, 3:13 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a30570cfd888190bfadf79c4cfcdb9b`	completed	June 15, 2026, 7:48 p.m.
NEDg	Description generation	`batch_6a31b9a482308190a82183f8bf571854`	completed	June 16, 2026, 9:01 p.m.
NED2	Entity disambiguation (via description)	`batch_6a33e21b231c8190860a4633feccc7fb`	completed	June 18, 2026, 12:18 p.m.

Created at: May 1, 2026, 12:45 a.m.