Triple

T4204631
Position Surface form Disambiguated ID Type / Status
Subject Buenos Aires Province E86153 entity
Predicate containsCity P294 FINISHED
Object Avellaneda E329768 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: Avellaneda | Statement: [Buenos Aires Province, containsCity, Avellaneda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avellaneda
Context triple: [Buenos Aires Province, containsCity, Avellaneda]
  • A. Avellaneda chosen
    Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
  • B. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • C. Almagro
    Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
  • D. Riva-Agüero
    Riva-Agüero is the family name of José de la Riva-Agüero, a prominent Peruvian politician and the first constitutionally elected president of Peru.
  • E. Ancud
    Ancud is a coastal city on northern Chiloé Island in southern Chile, known historically as a Spanish stronghold and for its maritime heritage and nearby natural landscapes.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0382eafc8190946bf45bf28095dd completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a19c90c819083a750fafa6fd1c7 completed March 14, 2026, 4:17 p.m.
Created at: March 9, 2026, 3:49 p.m.