Triple

T8106513
Position Surface form Disambiguated ID Type / Status
Subject Mount La Verna E189239 entity
Predicate near P350 FINISHED
Object Valtiberina
Valtiberina is a valley in central Italy, primarily in Tuscany and partly in Umbria, known for its scenic landscapes and historical towns along the upper Tiber River.
 E712535 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: Valtiberina | Statement: [Mount La Verna, near, Valtiberina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Valtiberina
Context triple: [Mount La Verna, near, Valtiberina]
  • A. Raeti
    The Raeti were an ancient Alpine people of central Europe, known from Roman sources for inhabiting the mountainous regions that later formed the Roman province of Raetia.
  • B. Vercellana
    Vercellana is an Italian surname most notably associated with Rosa Vercellana, the morganatic wife of King Victor Emmanuel II of Italy.
  • C. Maenza
    Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
  • D. Velino
    The Velino is a river in central Italy that flows through the province of Rieti before joining the Nera River near Terni.
  • E. Vespasia
    Vespasia was an ancient Roman family name associated with the noble lineage of the Vespasii, relatives of the emperor Vespasian.
  • 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: Valtiberina
Triple: [Mount La Verna, near, Valtiberina]
Generated description
Valtiberina is a valley in central Italy, primarily in Tuscany and partly in Umbria, known for its scenic landscapes and historical towns along the upper Tiber River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Valtiberina
Target entity description: Valtiberina is a valley in central Italy, primarily in Tuscany and partly in Umbria, known for its scenic landscapes and historical towns along the upper Tiber River.
  • A. Raeti
    The Raeti were an ancient Alpine people of central Europe, known from Roman sources for inhabiting the mountainous regions that later formed the Roman province of Raetia.
  • B. Vercellana
    Vercellana is an Italian surname most notably associated with Rosa Vercellana, the morganatic wife of King Victor Emmanuel II of Italy.
  • C. Maenza
    Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
  • D. Velino
    The Velino is a river in central Italy that flows through the province of Rieti before joining the Nera River near Terni.
  • E. Vespasia
    Vespasia was an ancient Roman family name associated with the noble lineage of the Vespasii, relatives of the emperor Vespasian.
  • 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_69ca82b9d5848190a24672775d5c5011 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb42f89dd481908f1a25e4b16a8fc8 completed March 31, 2026, 3:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc941075588190a9b12e2f873ba2a5 completed April 1, 2026, 3:42 a.m.
NEDg Description generation batch_69cc969e0ecc8190973658542d1406bc completed April 1, 2026, 3:53 a.m.
NED2 Entity disambiguation (via description) batch_69cc9771b6e48190bd5f45c3f8853890 completed April 1, 2026, 3:56 a.m.
Created at: March 30, 2026, 5:31 p.m.