Triple

T3408911
Position Surface form Disambiguated ID Type / Status
Subject Upper Peru E71842 entity
Predicate capital P234 FINISHED
Object Charcas E182607 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: Charcas | Statement: [Upper Peru, capital, Charcas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charcas
Context triple: [Upper Peru, capital, Charcas]
  • A. Charcas chosen
    Charcas is the former name of the Bolivian city now known as Sucre, a historic colonial center and constitutional capital of Bolivia.
  • B. Charjuy
    Charjuy is the former name of the city now known as Turkmenabat, a major urban center in eastern Turkmenistan.
  • C. Pasochoa
    Pasochoa is an extinct volcanic mountain in Ecuador known for its lush cloud forests and rich biodiversity within a protected ecological reserve.
  • D. Contadero
    Contadero is a residential and commercial neighborhood in the Cuajimalpa de Morelos borough of western Mexico City, known for its proximity to the Santa Fe business district and surrounding green areas.
  • E. Pitalito
    Pitalito is a major town and coffee-producing hub in southern Colombia, known as one of the country’s most important centers for high-quality coffee.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9056acc8190a9c50ec374851ac8 completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bdd99248190823875cae2531609 completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:15 p.m.