Triple

T2392198
Position Surface form Disambiguated ID Type / Status
Subject El Panecillo E48967 entity
Predicate partOf P40 FINISHED
Object Quito metropolitan area E8614 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: Quito metropolitan area | Statement: [El Panecillo, partOf, Quito metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quito metropolitan area
Context triple: [El Panecillo, partOf, Quito metropolitan area]
  • A. Quito chosen
    Quito is the high-altitude Andean city that serves as Ecuador’s political and cultural center, renowned for its well-preserved colonial historic center and dramatic mountain setting.
  • B. Cuenca
    Cuenca is a historic city in southern Ecuador known for its well-preserved colonial architecture and cultural significance.
  • C. Cuenca
    Cuenca is a historic Spanish city renowned for its medieval architecture and dramatic “hanging houses” perched above deep river gorges.
  • D. Guayaquil
    Guayaquil is a major Pacific port city in southwestern Ecuador and the country’s principal commercial and industrial center.
  • E. Metropolitan Area of Bogotá
    The Metropolitan Area of Bogotá is the large urban agglomeration centered on Colombia’s capital city, encompassing Bogotá and its surrounding municipalities in a closely integrated economic and commuter region.
  • 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_69a88aa5f63081908d07fd302029fcbd completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc87587708190a7f2bc473a898bc2 completed March 7, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69b28da24fe88190aabe2bcc520a35dc completed March 12, 2026, 9:55 a.m.
Created at: March 4, 2026, 7:57 p.m.