Triple

T17425996
Position Surface form Disambiguated ID Type / Status
Subject Department of Lima E423738 entity
Predicate hasMajorCity P316 FINISHED
Object Huaral NE NERFINISHED

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: Huaral | Statement: [Department of Lima, hasMajorCity, Huaral]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huaral
Context triple: [Department of Lima, hasMajorCity, Huaral]
  • A. Huaral chosen
    Huaral is a coastal agricultural city in central Peru known for its fruit production and proximity to Lima.
  • B. Yucay
    Yucay is a small Andean town in Peru’s Sacred Valley, known for its traditional agriculture, Inca terraces, and scenic mountain surroundings.
  • C. Huancané
    Huancané is a town in southern Peru that serves as an administrative and commercial center in the Puno region near Lake Titicaca.
  • D. Andahuaylas
    Andahuaylas is a city in the southern Peruvian Andes known as a commercial and cultural center for the surrounding rural highland communities.
  • E. Challapampa
    Challapampa is a small lakeside village on Bolivia’s Isla del Sol, known as a gateway to Inca ruins and scenic views over Lake Titicaca.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e448fbfda88190be1c001d64289bf7 completed April 19, 2026, 3:16 a.m.
Created at: April 10, 2026, 5:46 a.m.