Triple

T9640711
Position Surface form Disambiguated ID Type / Status
Subject Province of Pistoia E233056 entity
Predicate contains P35 FINISHED
Object Buggiano
Buggiano is a historic Tuscan town in central Italy known for its medieval architecture and scenic hillside setting.
 E826376 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: Buggiano | Statement: [Province of Pistoia, contains, Buggiano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Buggiano
Context triple: [Province of Pistoia, contains, Buggiano]
  • A. Pougny
    Pougny is a small French commune, likely located near the Swiss border in the Auvergne-Rhône-Alpes region.
  • B. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • C. Peypin
    Peypin is a small commune in the Bouches-du-Rhône department in southern France, located near Marseille in the Provence-Alpes-Côte d'Azur region.
  • D. Brière
    Brière is a French-language surname most prominently associated with former NHL player and current hockey executive Daniel Brière.
  • E. Montbéliard
    Montbéliard is a historic town in eastern France, near the Swiss border, known for its former status as a Württemberg principality and its distinctive blend of French and German cultural influences.
  • 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: Buggiano
Triple: [Province of Pistoia, contains, Buggiano]
Generated description
Buggiano is a historic Tuscan town in central Italy known for its medieval architecture and scenic hillside setting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Buggiano
Target entity description: Buggiano is a historic Tuscan town in central Italy known for its medieval architecture and scenic hillside setting.
  • A. Pougny
    Pougny is a small French commune, likely located near the Swiss border in the Auvergne-Rhône-Alpes region.
  • B. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • C. Peypin
    Peypin is a small commune in the Bouches-du-Rhône department in southern France, located near Marseille in the Provence-Alpes-Côte d'Azur region.
  • D. Brière
    Brière is a French-language surname most prominently associated with former NHL player and current hockey executive Daniel Brière.
  • E. Montbéliard
    Montbéliard is a historic town in eastern France, near the Swiss border, known for its former status as a Württemberg principality and its distinctive blend of French and German cultural influences.
  • 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_69ca848a5a908190aad251f4137b0c3a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b552a1c81909a1fab347110eeb1 completed April 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1e3f04358819098b2cef9272cbc19 completed April 5, 2026, 4:24 a.m.
NEDg Description generation batch_69d1e6372cec8190b7d6b32da197d89c completed April 5, 2026, 4:33 a.m.
NED2 Entity disambiguation (via description) batch_69d1e6af89f88190abe63f8172182f58 completed April 5, 2026, 4:35 a.m.
Created at: March 30, 2026, 8:12 p.m.