Triple

T1761817
Position Surface form Disambiguated ID Type / Status
Subject Latium E38673 entity
Predicate borders P224 FINISHED
Object Sabina
Sabina is a historical region of central Italy, traditionally inhabited by the Sabines and known for its rugged landscape and proximity to ancient Rome.
 E203655 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: Sabina | Statement: [Latium, borders, Sabina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sabina
Context triple: [Latium, borders, Sabina]
  • A. Sabine
    Sabine is a surname most notably associated with Wallace Clement Sabine, the American physicist who founded the field of architectural acoustics.
  • B. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • C. Sara
    Sara is a language spoken in parts of Central Africa, particularly in Chad.
  • D. Sara
    Sara is a feminine given name of Hebrew origin meaning "princess," historically borne by notable figures including Sara Ann Delano Roosevelt, the mother of U.S. President Franklin D. Roosevelt.
  • E. Katia
    Katia is the Atlantic hurricane name that was introduced to replace the retired name Katrina following the devastating 2005 storm.
  • 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: Sabina
Triple: [Latium, borders, Sabina]
Generated description
Sabina is a historical region of central Italy, traditionally inhabited by the Sabines and known for its rugged landscape and proximity to ancient Rome.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sabina
Target entity description: Sabina is a historical region of central Italy, traditionally inhabited by the Sabines and known for its rugged landscape and proximity to ancient Rome.
  • A. Sabine
    Sabine is a surname most notably associated with Wallace Clement Sabine, the American physicist who founded the field of architectural acoustics.
  • B. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • C. Sara
    Sara is a language spoken in parts of Central Africa, particularly in Chad.
  • D. Sara
    Sara is a feminine given name of Hebrew origin meaning "princess," historically borne by notable figures including Sara Ann Delano Roosevelt, the mother of U.S. President Franklin D. Roosevelt.
  • E. Katia
    Katia is the Atlantic hurricane name that was introduced to replace the retired name Katrina following the devastating 2005 storm.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6463ac0081909e9ebe6ebf1db857 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf4db1c48190a96f137db3e2f32c completed March 8, 2026, 6:26 p.m.
NEDg Description generation batch_69adc0a3fdd88190b0ffa98db1b5cf80 completed March 8, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_69adc12c894881909c9a82fc9e363a41 completed March 8, 2026, 6:34 p.m.
Created at: March 4, 2026, 7:31 p.m.