Triple

T10294318
Position Surface form Disambiguated ID Type / Status
Subject Machala E241443 entity
Predicate roadConnectionTo P9041 FINISHED
Object Cuenca E133952 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: Cuenca | Statement: [Machala, roadConnectionTo, Cuenca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuenca
Context triple: [Machala, roadConnectionTo, Cuenca]
  • A. Cuenca
    Cuenca is a historic Spanish city renowned for its medieval architecture and dramatic “hanging houses” perched above deep river gorges.
  • B. Cuenca chosen
    Cuenca is a historic city in southern Ecuador known for its well-preserved colonial architecture and cultural significance.
  • C. Cuenca
    Cuenca is a landlocked municipality in the province of Batangas in the Philippines, known for Mount Macolod and its agricultural communities.
  • D. Calarcá
    Calarcá is a Colombian town and municipality in the coffee-growing Quindío Department, known for its cultural heritage and role in the Coffee Cultural Landscape.
  • E. Suesca
    Suesca is a Colombian town in the department of Cundinamarca, renowned for its dramatic rock cliffs that make it a popular destination for rock climbing and outdoor recreation.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2d5e0f88190be3e23ba2511a1e9 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d1c180481909ca9983e14cbb931 completed April 9, 2026, 3:29 a.m.
Created at: April 6, 2026, 11:42 a.m.