Triple

T5973005
Position Surface form Disambiguated ID Type / Status
Subject Tata Martino E132919 entity
Predicate playedFor P2170 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: [Tata Martino, playedFor, Lanús]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lanús
Context triple: [Tata Martino, playedFor, 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. Barracas
    Barracas is a traditional working-class neighborhood in Buenos Aires, Argentina, known for its historic architecture, industrial past, and strong local identity.
  • D. Tres de Febrero
    Tres de Febrero is a partido (administrative district) in the Greater Buenos Aires metropolitan area of Argentina, known for its dense urban character and proximity to the city of Buenos Aires.
  • E. San Nicolás de los Arroyos
    San Nicolás de los Arroyos is an industrial and port city in the Buenos Aires Province of Argentina, known for its manufacturing sector and strategic location on the Paraná River.
  • 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_69c0086deab081908550159ca23eec9b completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a00c3588190b335d7d3341b6d68 completed March 22, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c108422220819092ac63e5ebb264b4 completed March 23, 2026, 9:30 a.m.
Created at: March 22, 2026, 4:03 p.m.