Triple

T11490083
Position Surface form Disambiguated ID Type / Status
Subject Narvarte E272382 entity
Predicate hasSubdivision P747 FINISHED
Object Narvarte Oriente E272382 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: Narvarte Oriente | Statement: [Narvarte, hasSubdivision, Narvarte Oriente]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Narvarte Oriente
Context triple: [Narvarte, hasSubdivision, Narvarte Oriente]
  • A. Narvarte Poniente
    Narvarte Poniente is a residential and commercial neighborhood in Mexico City’s Benito Juárez borough, known for its central location, urban amenities, and proximity to major avenues and metro stations.
  • B. Narvarte chosen
    Narvarte is a centrally located neighborhood in Mexico City known for its residential character, mid-20th-century architecture, and growing array of restaurants, cafes, and nightlife.
  • C. La Payunia
    La Payunia is an extensive volcanic field in Argentina renowned for its numerous cinder cones, lava flows, and striking black volcanic landscapes.
  • D. Navarrenx
    Navarrenx is a historic fortified town in southwestern France, known for its well-preserved ramparts and strategic position in the Béarn region.
  • E. Tasqueña
    Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
  • 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85a20df608190992543b4d7006f8a completed April 10, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69e624c3691081908f2e448aebab40aa completed April 20, 2026, 1:06 p.m.
Created at: April 8, 2026, 9:36 p.m.