Triple

T27267228

Position	Surface form	Disambiguated ID	Type / Status
Subject	Val di Cecina	`E687935`	entity
Predicate	hasTransportConnection	`P845`	FINISHED
Object	Aurelia road Aurelia road is a major Italian coastal highway running along the Tyrrhenian coast and connecting numerous towns and regions in central and western Italy.	`E2291321`	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: Aurelia road | Statement: [Val di Cecina, hasTransportConnection, Aurelia road]

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: Aurelia road
Triple: [Val di Cecina, hasTransportConnection, Aurelia road]

Generated description

Aurelia road is a major Italian coastal highway running along the Tyrrhenian coast and connecting numerous towns and regions in central and western Italy.

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_69ef3557abc481908bf3c146f0f3356a`	completed	April 27, 2026, 10:07 a.m.
NER	Named-entity recognition	`batch_69f626f45a1481909200fc3f7fda8a61`	completed	May 2, 2026, 4:31 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a5c4919d4a08190a7bb8ff08dbcb4a2`	completed	July 19, 2026, 3:48 a.m.
NEDg	Description generation	`batch_6a5c49ead6748190bffce60b24716acb`	completed	July 19, 2026, 3:52 a.m.
NED2	Entity disambiguation (via description)	`batch_6a5c4aa384e88190bf48e076738c0b07`	completed	July 19, 2026, 3:55 a.m.

Created at: April 27, 2026, 10:56 a.m.