Triple

T3274901
Position Surface form Disambiguated ID Type / Status
Subject Province of Rieti E68735 entity
Predicate contains P35 FINISHED
Object Borbona
Borbona is a small Italian town and comune in the Lazio region, known for its rural setting in the Apennine mountains and traditional local culture.
E344552 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: Borbona | Statement: [Province of Rieti, contains, Borbona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borbona
Context triple: [Province of Rieti, contains, Borbona]
  • A. Carlota
    Carlota is the feminine given name corresponding to Carlos, commonly used in Spanish- and Portuguese-speaking cultures.
  • B. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • C. Isabela
    Isabela is a large agricultural province in the Cagayan Valley region of the Philippines, known especially for its extensive rice and corn production.
  • D. Josefa de Tudó
    Josefa de Tudó was a Spanish noblewoman best known as the longtime mistress and later wife of Manuel Godoy, a powerful favorite of King Charles IV.
  • E. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • 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: Borbona
Triple: [Province of Rieti, contains, Borbona]
Generated description
Borbona is a small Italian town and comune in the Lazio region, known for its rural setting in the Apennine mountains and traditional local culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Borbona
Target entity description: Borbona is a small Italian town and comune in the Lazio region, known for its rural setting in the Apennine mountains and traditional local culture.
  • A. Carlota
    Carlota is the feminine given name corresponding to Carlos, commonly used in Spanish- and Portuguese-speaking cultures.
  • B. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • C. Isabela
    Isabela is a large agricultural province in the Cagayan Valley region of the Philippines, known especially for its extensive rice and corn production.
  • D. Josefa de Tudó
    Josefa de Tudó was a Spanish noblewoman best known as the longtime mistress and later wife of Manuel Godoy, a powerful favorite of King Charles IV.
  • E. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adaff8a440819092509bc8511b2785 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e841d5588190a53ba90a46721b0f completed March 12, 2026, 4:22 p.m.
NEDg Description generation batch_69b2e8b79d308190922a310ff1337eae completed March 12, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_69b2e9ba41948190b9e4f6f54f32603c completed March 12, 2026, 4:28 p.m.
Created at: March 8, 2026, 3:10 p.m.