Triple

T5220846
Position Surface form Disambiguated ID Type / Status
Subject Province of Livorno E117863 entity
Predicate contains P35 FINISHED
Object Cecina
Cecina is a coastal town in Tuscany, Italy, known for its beaches, tourism, and proximity to the Tyrrhenian Sea.
 E504121 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: Cecina | Statement: [Province of Livorno, contains, Cecina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cecina
Context triple: [Province of Livorno, contains, Cecina]
  • A. Narón
    Narón is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its close ties to the nearby city of Ferrol and its role in the region’s industrial and service economy.
  • B. Santena
    Santena is a small town in the Piedmont region of northern Italy, known for its historical association with statesman Camillo Benso, Count of Cavour.
  • C. Cannigione
    Cannigione is a coastal village and popular tourist resort in northern Sardinia, Italy, known for its beaches and marina overlooking the Gulf of Arzachena.
  • D. Enza
    Enza is a river in northern Italy that flows through the Emilia-Romagna region before joining the Secchia.
  • E. Osona
    Osona is a historical inland comarca in Catalonia, Spain, known for its rural landscapes, medieval towns, and the city of Vic as its main urban center.
  • 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: Cecina
Triple: [Province of Livorno, contains, Cecina]
Generated description
Cecina is a coastal town in Tuscany, Italy, known for its beaches, tourism, and proximity to the Tyrrhenian Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cecina
Target entity description: Cecina is a coastal town in Tuscany, Italy, known for its beaches, tourism, and proximity to the Tyrrhenian Sea.
  • A. Narón
    Narón is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its close ties to the nearby city of Ferrol and its role in the region’s industrial and service economy.
  • B. Santena
    Santena is a small town in the Piedmont region of northern Italy, known for its historical association with statesman Camillo Benso, Count of Cavour.
  • C. Cannigione
    Cannigione is a coastal village and popular tourist resort in northern Sardinia, Italy, known for its beaches and marina overlooking the Gulf of Arzachena.
  • D. Enza
    Enza is a river in northern Italy that flows through the Emilia-Romagna region before joining the Secchia.
  • E. Osona
    Osona is a historical inland comarca in Catalonia, Spain, known for its rural landscapes, medieval towns, and the city of Vic as its main urban center.
  • 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_69bd4465e03081909bfcfd7113062590 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7ab846548190bcd2c5cd238f6cd9 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69beeff49d708190a042dfab473a9646 completed March 21, 2026, 7:22 p.m.
NEDg Description generation batch_69bef309c230819094ed6ae3fefe6e5b completed March 21, 2026, 7:35 p.m.
NED2 Entity disambiguation (via description) batch_69bef36c88f4819082931dbe1bb13f89 completed March 21, 2026, 7:37 p.m.
Created at: March 20, 2026, 1:48 p.m.