Triple

T10174381
Position Surface form Disambiguated ID Type / Status
Subject Province of Massa-Carrara E235812 entity
Predicate contains P35 FINISHED
Object Bagnone
Bagnone is a small historic town in northern Tuscany, Italy, known for its medieval architecture and scenic setting in the Lunigiana region.
E848299 NE FINISHED

How this triple was built (4 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: Bagnone | Statement: [Province of Massa-Carrara, contains, Bagnone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bagnone
Context triple: [Province of Massa-Carrara, contains, Bagnone]
  • A. Bagnacavallo
    Bagnacavallo is a historic town in Italy’s Emilia-Romagna region, known for its well-preserved medieval center and traditional rural culture.
  • B. Lesignano
    Lesignano is a locality or subdivision within the municipality of Serravalle in San Marino.
  • C. Capannori
    Capannori is a municipality in Tuscany, central Italy, known for its agricultural landscape, historic villas, and pioneering zero-waste environmental policies.
  • D. Careggine
    Careggine is a small mountain village and comune in Tuscany, central Italy, known for its scenic Apennine setting and traditional rural character.
  • E. Sarzana
    Sarzana is a historic town in the Liguria region of northwestern Italy, known for its medieval fortifications and strategic position near the border with Tuscany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Bagnone
Triple: [Province of Massa-Carrara, contains, Bagnone]
Generated description
Bagnone is a small historic town in northern Tuscany, Italy, known for its medieval architecture and scenic setting in the Lunigiana region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bagnone
Target entity description: Bagnone is a small historic town in northern Tuscany, Italy, known for its medieval architecture and scenic setting in the Lunigiana region.
  • A. Bagnacavallo
    Bagnacavallo is a historic town in Italy’s Emilia-Romagna region, known for its well-preserved medieval center and traditional rural culture.
  • B. Lesignano
    Lesignano is a locality or subdivision within the municipality of Serravalle in San Marino.
  • C. Capannori
    Capannori is a municipality in Tuscany, central Italy, known for its agricultural landscape, historic villas, and pioneering zero-waste environmental policies.
  • D. Careggine
    Careggine is a small mountain village and comune in Tuscany, central Italy, known for its scenic Apennine setting and traditional rural character.
  • E. Sarzana
    Sarzana is a historic town in the Liguria region of northwestern Italy, known for its medieval fortifications and strategic position near the border with Tuscany.
  • F. None of above. chosen

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_69ca84d1d5f88190ab878a1021ecff68 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdeca0dc508190916f2a1bbb288192 completed April 2, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d355075c0c819090854c1408681975 completed April 6, 2026, 6:39 a.m.
NEDg Description generation batch_69d356321ca88190baa12d4c25fbf393 completed April 6, 2026, 6:44 a.m.
NED2 Entity disambiguation (via description) batch_69d3568953588190bc19f57da2a6b44a completed April 6, 2026, 6:45 a.m.
Created at: March 30, 2026, 9:11 p.m.