Triple

T4300252
Position Surface form Disambiguated ID Type / Status
Subject Pierfrancesco Favino E99816 entity
Predicate notableWork P4 FINISHED
Object Suburra
Suburra is a 2015 Italian crime film that explores the violent intersection of politics, organized crime, and real estate corruption in Rome.
 E428547 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: Suburra | Statement: [Pierfrancesco Favino, notableWork, Suburra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Suburra
Context triple: [Pierfrancesco Favino, notableWork, Suburra]
  • A. Majadahonda
    Majadahonda is a suburban municipality west of Madrid, Spain, known for its residential character, shopping centers, and sports facilities.
  • B. La Rinconada
    La Rinconada is a municipality in the province of Seville, Spain, situated just north of the city of Seville in the Andalusia region.
  • C. El Molo
    El Molo is a nearly extinct Cushitic language spoken by the El Molo people of northern Kenya along the shores of Lake Turkana.
  • D. Mogotón
    Mogotón is a mountain on the border between Nicaragua and Honduras that forms the highest peak in Nicaragua.
  • E. Calle 2 Sur
    Calle 2 Sur is a central street in the historic downtown of Puebla, Mexico, running near the city’s main square and colonial landmarks.
  • 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: Suburra
Triple: [Pierfrancesco Favino, notableWork, Suburra]
Generated description
Suburra is a 2015 Italian crime film that explores the violent intersection of politics, organized crime, and real estate corruption in Rome.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Suburra
Target entity description: Suburra is a 2015 Italian crime film that explores the violent intersection of politics, organized crime, and real estate corruption in Rome.
  • A. Majadahonda
    Majadahonda is a suburban municipality west of Madrid, Spain, known for its residential character, shopping centers, and sports facilities.
  • B. La Rinconada
    La Rinconada is a municipality in the province of Seville, Spain, situated just north of the city of Seville in the Andalusia region.
  • C. El Molo
    El Molo is a nearly extinct Cushitic language spoken by the El Molo people of northern Kenya along the shores of Lake Turkana.
  • D. Mogotón
    Mogotón is a mountain on the border between Nicaragua and Honduras that forms the highest peak in Nicaragua.
  • E. Calle 2 Sur
    Calle 2 Sur is a central street in the historic downtown of Puebla, Mexico, running near the city’s main square and colonial landmarks.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509e8cb481909ccca7992aac31a3 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c74a1a7c8190a69a82a8a2a38db9 completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c7d04508819087b14c5c86f1e015 completed March 14, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69b5c84ccea08190a8e7e8fa93934ea2 completed March 14, 2026, 8:42 p.m.
Created at: March 12, 2026, 11:08 p.m.