Triple

T25833620
Position Surface form Disambiguated ID Type / Status
Subject Porta San Giorgio area E650730 entity
Predicate nearbyAttraction P3449 FINISHED
Object San Niccolò district
The San Niccolò district is a historic neighborhood in Florence, Italy, known for its charming medieval streets, artisan workshops, and scenic views near the Arno River and Piazzale Michelangelo.
E1698450 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: San Niccolò district | Statement: [Porta San Giorgio area, nearbyAttraction, San Niccolò district]
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: San Niccolò district
Triple: [Porta San Giorgio area, nearbyAttraction, San Niccolò district]
Generated description
The San Niccolò district is a historic neighborhood in Florence, Italy, known for its charming medieval streets, artisan workshops, and scenic views near the Arno River and Piazzale Michelangelo.

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_69e7ab37438081908f1ccf6284839520 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f601f374308190aebe5dcc12105514 completed May 2, 2026, 1:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10da2bfb1081908a6cedd5cf264ec7 completed May 22, 2026, 10:35 p.m.
NEDg Description generation batch_6a10de2035e081908bc333d5b3a4f5ae completed May 22, 2026, 10:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10de90e8a88190a13001d313e5a588 completed May 22, 2026, 10:54 p.m.
Created at: April 22, 2026, 7:39 a.m.