Triple

T5955132
Position Surface form Disambiguated ID Type / Status
Subject National Route 3 E132493 entity
Predicate passesThrough P225 FINISHED
Object Bahía Blanca E431330 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: Bahía Blanca | Statement: [National Route 3, passesThrough, Bahía Blanca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bahía Blanca
Context triple: [National Route 3, passesThrough, Bahía Blanca]
  • A. Bahía Blanca chosen
    Bahía Blanca is a major port city in southern Buenos Aires Province, Argentina, known for its industrial activity and strategic location on the Atlantic coast.
  • B. Mar del Plata
    Mar del Plata is a major Argentine Atlantic coastal city renowned as a popular beach resort and tourist destination.
  • C. Comodoro Rivadavia
    Comodoro Rivadavia is a coastal city in southern Argentina known as a key oil industry hub and one of the main urban centers of Patagonia.
  • D. Gualeguaychú
    Gualeguaychú is a city in eastern Argentina known for its vibrant Carnival celebrations and riverside tourism.
  • E. Colonia Buenos Aires
    Colonia Buenos Aires is a neighborhood located within the Cuauhtémoc borough in central Mexico City.
  • 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_69c0086b05cc8190a8f36a96927a525c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c039c054a48190ace32250c43e29b4 completed March 22, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c518b75da08190829e7e746f99f5ac completed March 26, 2026, 11:29 a.m.
Created at: March 22, 2026, 4:02 p.m.