Triple

T3242266
Position Surface form Disambiguated ID Type / Status
Subject Province of Frosinone E67988 entity
Predicate contains P35 FINISHED
Object Ferentino
Ferentino is a historic hill town in the Lazio region of central Italy, known for its ancient Roman and medieval architecture.
 E339645 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: Ferentino | Statement: [Province of Frosinone, contains, Ferentino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ferentino
Context triple: [Province of Frosinone, contains, Ferentino]
  • A. Gavignano
    Gavignano is a small Italian town in the Lazio region, historically notable as the birthplace of Pope Innocent III.
  • B. Quarracino
    Quarracino is an Italian-origin surname most notably associated with Argentine Cardinal Antonio Quarracino.
  • C. Caudini
    The Caudini were an ancient Italic people forming one of the principal tribes of the Samnite confederation in southern Italy.
  • D. Caprile
    Caprile is a surname associated with the architectural firm Lohan Caprile Goettsch Architects.
  • E. Valperga
    Valperga is a historical novel by Mary Shelley that reimagines the life and times of the 14th-century Italian warlord Castruccio Castracani through a blend of romance, politics, and philosophical reflection.
  • 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: Ferentino
Triple: [Province of Frosinone, contains, Ferentino]
Generated description
Ferentino is a historic hill town in the Lazio region of central Italy, known for its ancient Roman and medieval architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ferentino
Target entity description: Ferentino is a historic hill town in the Lazio region of central Italy, known for its ancient Roman and medieval architecture.
  • A. Gavignano
    Gavignano is a small Italian town in the Lazio region, historically notable as the birthplace of Pope Innocent III.
  • B. Quarracino
    Quarracino is an Italian-origin surname most notably associated with Argentine Cardinal Antonio Quarracino.
  • C. Caudini
    The Caudini were an ancient Italic people forming one of the principal tribes of the Samnite confederation in southern Italy.
  • D. Caprile
    Caprile is a surname associated with the architectural firm Lohan Caprile Goettsch Architects.
  • E. Valperga
    Valperga is a historical novel by Mary Shelley that reimagines the life and times of the 14th-century Italian warlord Castruccio Castracani through a blend of romance, politics, and philosophical reflection.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf17463481909447f6ab46016407 completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b27757dff0819081a26aea52ede49d completed March 12, 2026, 8:20 a.m.
NEDg Description generation batch_69b27846372c8190a5c96158bf2a5ff2 completed March 12, 2026, 8:24 a.m.
NED2 Entity disambiguation (via description) batch_69b2791ac4a08190a1cee3cfbca6e6d6 completed March 12, 2026, 8:28 a.m.
Created at: March 8, 2026, 3:08 p.m.