Triple

T13729913
Position Surface form Disambiguated ID Type / Status
Subject Avellaneda E329768 entity
Predicate borderedBy P224 FINISHED
Object Lanús E434501 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: Lanús | Statement: [Avellaneda, borderedBy, Lanús]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lanús
Context triple: [Avellaneda, borderedBy, Lanús]
  • A. Lanús chosen
    Lanús is a city in the Greater Buenos Aires metropolitan area of Argentina, known as an important industrial and residential center and as the home of the football club Club Atlético Lanús.
  • B. Morón
    Morón is a city in the western part of the Greater Buenos Aires metropolitan area in Argentina, known as an important residential and commercial hub.
  • C. Vicente López
    Vicente López is a suburban partido (district) in the northern Greater Buenos Aires area of Argentina, known for its residential neighborhoods and riverside parks along the Río de la Plata.
  • D. Barracas
    Barracas is a traditional working-class neighborhood in Buenos Aires, Argentina, known for its historic architecture, industrial past, and strong local identity.
  • E. Morón city
    Morón city is an urban center in central Cuba known historically for its sugar industry and as a gateway to nearby northern cays and beach resorts.
  • 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_69d80772315881908f980cae40d91664 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69de01f746cc8190abde237bbb7e6c78 completed April 14, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f79d65062c819086a5f7a7ebc45412 completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:55 p.m.