Triple

T32811874
Position Surface form Disambiguated ID Type / Status
Subject Basilica of San Ponziano E839174 entity
Predicate hasViewOf P854 FINISHED
Object Spoleto valley
The Spoleto valley is a scenic Umbrian valley in central Italy, known for its rolling hills, historic towns, and views dominated by the ancient city of Spoleto.
E2025392 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: Spoleto valley | Statement: [Basilica of San Ponziano, hasViewOf, Spoleto valley]
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: Spoleto valley
Triple: [Basilica of San Ponziano, hasViewOf, Spoleto valley]
Generated description
The Spoleto valley is a scenic Umbrian valley in central Italy, known for its rolling hills, historic towns, and views dominated by the ancient city of Spoleto.

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_69f3493d35208190b4351b4e85f2fa16 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cdc9ecc88190bac7794750c5ce6c completed May 3, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34bcf232f481909e3c232db55a7978 completed June 19, 2026, 3:52 a.m.
NEDg Description generation batch_6a34bda4d1308190932b182fc3daee1f completed June 19, 2026, 3:55 a.m.
NED2 Entity disambiguation (via description) batch_6a34be49d2c0819089cb85ac34fa49ca completed June 19, 2026, 3:58 a.m.
Created at: May 1, 2026, 1:15 a.m.