Triple

T6362444
Position Surface form Disambiguated ID Type / Status
Subject Ecclesiastical province of La Serena E143142 entity
Predicate hasCathedralCity P9022 FINISHED
Object La Serena E503 NE FINISHED

How this triple was built (2 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: La Serena | Statement: [Ecclesiastical province of La Serena, hasCathedralCity, La Serena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Serena
Context triple: [Ecclesiastical province of La Serena, hasCathedralCity, La Serena]
  • A. La Serena chosen
    La Serena is a coastal city in northern Chile known for its colonial architecture, beaches, and role as a gateway to major astronomical observatories in the region.
  • B. Vallenar
    Vallenar is a city in northern Chile known as an agricultural and mining center in the Atacama Desert.
  • C. Maipú
    Maipú is a populous commune and suburb of Santiago, Chile, known for its residential areas, commercial activity, and historical significance in the Santiago Metropolitan Region.
  • D. Maipú
    Maipú is a renowned wine-producing region in Argentina’s Mendoza Province, noted for its high-quality Malbec and other varietals.
  • E. Valparaíso
    Valparaíso is a major Pacific port city in central Chile, renowned for its steep hillsides, colorful houses, historic funiculars, and UNESCO-listed historic quarter.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c008d7a9c4819098d647ec47776917 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0680c02b481908618317566e31a5c completed March 22, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bab02948190bc64bb0b96a55602 completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:32 p.m.