Triple

T34276719
Position Surface form Disambiguated ID Type / Status
Subject Segni E879476 entity
Predicate hasReligiousBuilding P1191 FINISHED
Object Cathedral of Santa Maria Assunta
The Cathedral of Santa Maria Assunta is the principal Roman Catholic church in the town of Segni, Italy, notable for its historic architecture and religious significance.
E2089335 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: Cathedral of Santa Maria Assunta | Statement: [Segni, hasReligiousBuilding, Cathedral of Santa Maria Assunta]
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: Cathedral of Santa Maria Assunta
Triple: [Segni, hasReligiousBuilding, Cathedral of Santa Maria Assunta]
Generated description
The Cathedral of Santa Maria Assunta is the principal Roman Catholic church in the town of Segni, Italy, notable for its historic architecture and religious significance.

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_69f349b5f6648190b9420d94a4cd16e0 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f712eb74408190b0b9818f5a1916fe completed May 3, 2026, 9:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36e627db3881908e5c82f3d1a5463d completed June 20, 2026, 7:12 p.m.
NEDg Description generation batch_6a36e94d06408190ac162fa97676063f completed June 20, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a36e9d01960819085bccf4bff119b09 completed June 20, 2026, 7:28 p.m.
Created at: May 1, 2026, 1:56 a.m.