Triple

T3221527
Position Surface form Disambiguated ID Type / Status
Subject Province of Latina E67521 entity
Predicate contains P35 FINISHED
Object Maenza
Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
 E339381 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: Maenza | Statement: [Province of Latina, contains, Maenza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maenza
Context triple: [Province of Latina, contains, Maenza]
  • A. Rumuola
    Rumuola is a prominent urban neighborhood and transport hub in Port Harcourt, Rivers State, Nigeria.
  • B. Menetes
    Menetes is a genus of rodents in the squirrel family, comprising ground-dwelling squirrels native to parts of Asia.
  • C. Hoschedé
    Hoschedé is a French surname notably associated with the family closely linked to Impressionist painter Claude Monet.
  • D. Clusium
    Clusium was an important ancient Etruscan city, known for its strategic location in central Italy and its significant role in early Roman history.
  • E. Sabinum
    Sabinum was the ancient central Italian region traditionally associated with the Sabine people, located in the Apennine area northeast of Rome.
  • 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: Maenza
Triple: [Province of Latina, contains, Maenza]
Generated description
Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maenza
Target entity description: Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
  • A. Rumuola
    Rumuola is a prominent urban neighborhood and transport hub in Port Harcourt, Rivers State, Nigeria.
  • B. Menetes
    Menetes is a genus of rodents in the squirrel family, comprising ground-dwelling squirrels native to parts of Asia.
  • C. Hoschedé
    Hoschedé is a French surname notably associated with the family closely linked to Impressionist painter Claude Monet.
  • D. Clusium
    Clusium was an important ancient Etruscan city, known for its strategic location in central Italy and its significant role in early Roman history.
  • E. Sabinum
    Sabinum was the ancient central Italian region traditionally associated with the Sabine people, located in the Apennine area northeast of Rome.
  • 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_69ad858b8adc8190ad989712c87a476b completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adae1845408190b3eccd791231c69c completed March 8, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2771be134819081809b2351517fdf completed March 12, 2026, 8:19 a.m.
NEDg Description generation batch_69b27844c6708190ac61f00a74a2ef27 completed March 12, 2026, 8:24 a.m.
NED2 Entity disambiguation (via description) batch_69b27911ff1481908a36f279a871c510 completed March 12, 2026, 8:28 a.m.
Created at: March 8, 2026, 3:08 p.m.