Triple

T28987073
Position Surface form Disambiguated ID Type / Status
Subject Arpino E734716 entity
Predicate hasLandmark P105 FINISHED
Object Church of San Michele Arcangelo
The Church of San Michele Arcangelo is a historic Catholic church in Arpino, Italy, dedicated to Saint Michael the Archangel and notable for its religious and artistic heritage.
E1846231 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: Church of San Michele Arcangelo | Statement: [Arpino, hasLandmark, Church of San Michele Arcangelo]
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: Church of San Michele Arcangelo
Triple: [Arpino, hasLandmark, Church of San Michele Arcangelo]
Generated description
The Church of San Michele Arcangelo is a historic Catholic church in Arpino, Italy, dedicated to Saint Michael the Archangel and notable for its religious and artistic 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_69f05b0dd9b481908b7901e1c95ff6b2 completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65f7a782081909a7915941423bdd3 completed May 2, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2505b41b548190b9f2dcd09f3ae4f4 completed June 7, 2026, 5:46 a.m.
NEDg Description generation batch_6a250a0727108190bc085f034870e22e completed June 7, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a250f52bc788190a19327674f832883 completed June 7, 2026, 6:27 a.m.
Created at: April 28, 2026, 9:15 a.m.