Triple

T2394876
Position Surface form Disambiguated ID Type / Status
Subject Illapel E47625 entity
Predicate regionCapital P16248 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: [Illapel, regionCapital, La Serena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Serena
Context triple: [Illapel, regionCapital, 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. Vallenar
    Vallenar is a city in northern Chile known as an agricultural and mining center in the Atacama Desert.
  • C. Maipú
    Maipú is a renowned wine-producing region in Argentina’s Mendoza Province, noted for its high-quality Malbec and other varietals.
  • D. Maipú
    Maipú is a populous commune and suburb of Santiago, Chile, known for its residential areas, commercial activity, and historical significance in the Santiago Metropolitan Region.
  • E. 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.
  • 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_69a88a1c450c81909f61abb8b6863885 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc87827d88190bb2351a688e6de32 completed March 7, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2356752c08190aac1b36f6c14ad8c completed March 12, 2026, 3:39 a.m.
Created at: March 4, 2026, 7:57 p.m.