Triple

T778290
Position Surface form Disambiguated ID Type / Status
Subject La Florida Airport E16438 entity
Predicate locatedInCity P40 FINISHED
Object La Serena E503 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: La Serena | Statement: [La Florida Airport, locatedInCity, La Serena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Serena
Context triple: [La Florida Airport, locatedInCity, La Serena]
  • A. La Serena chosen
    La Serena is a coastal city in northern Chile known for its colonial architecture, beaches, and role as a gateway to major astronomical observatories in the region.
  • B. Valparaíso
    Valparaíso is a major Pacific port city in central Chile, renowned for its steep hillsides, colorful houses, historic funiculars, and UNESCO-listed historic quarter.
  • C. Concepción
    Concepción was one of the ships in Ferdinand Magellan’s expedition that took part in the first circumnavigation of the globe.
  • D. Concepción
    Concepción is an active stratovolcano located on Ometepe Island in Lake Nicaragua, known for its symmetrical cone shape and frequent eruptions.
  • E. Concepción
    Concepción is a major Chilean city in the south-central part of the country, known as an important industrial, commercial, and educational center.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a74f886081909c27b786e3adbe32 completed March 1, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3b978de4819083b117ee3a6cb8c1 completed March 7, 2026, 2:52 p.m.
Created at: March 1, 2026, 7:37 p.m.