Triple

T7958517
Position Surface form Disambiguated ID Type / Status
Subject Caquetá Department E184801 entity
Predicate largestCity P235 FINISHED
Object Florencia E703998 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: Florencia | Statement: [Caquetá Department, largestCity, Florencia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florencia
Context triple: [Caquetá Department, largestCity, Florencia]
  • A. Florencia
    Florencia is a street in Mexico City that intersects at the Glorieta del Ángel, a major roundabout surrounding the iconic Angel of Independence monument.
  • B. Florencia chosen
    Florencia is a city in southern Colombia that serves as a key gateway between the Andean region and the Amazon rainforest.
  • C. San Juan de Flores
    San Juan de Flores is a municipality in central Honduras known for its rural character and location within the Francisco Morazán Department.
  • D. Concepción
    Concepción is a major Chilean city in the south-central part of the country, known as an important industrial, commercial, and educational center.
  • E. Concepción
    Concepción was one of the ships in Ferdinand Magellan’s expedition that took part in the first circumnavigation of the globe.
  • 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_69ca8293a2388190aace944d7ed9c0c0 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b80050c81909b2db95ade495052 completed March 31, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc565efef48190915892c5d8af852c completed March 31, 2026, 11:18 p.m.
Created at: March 30, 2026, 5:11 p.m.