Triple

T851642
Position Surface form Disambiguated ID Type / Status
Subject Biobío Region E18398 entity
Predicate containsCity P294 FINISHED
Object Arauco
Arauco is a coastal city and commune in Chile known for its forestry industry and location within the Biobío Region.
E107568 NE FINISHED

How this triple was built (4 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: Arauco | Statement: [Biobío Region, containsCity, Arauco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arauco
Context triple: [Biobío Region, containsCity, Arauco]
  • A. Andacollo
    Andacollo is a small mining town and municipality in Chile’s Coquimbo Region, known for its copper deposits and the religious shrine of the Virgin of Andacollo.
  • B. Talcahuano
    Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
  • C. Pudahuel
    Pudahuel is a commune in the Santiago Metropolitan Region of Chile, known for hosting the country’s main international airport and forming part of the greater Santiago urban area.
  • D. Quirihue
    Quirihue is a small city in central Chile that serves as the capital of the Itata Province in the Ñuble Region.
  • E. Aysén Region
    The Aysén Region is a sparsely populated, fjord-filled and mountainous administrative region in southern Chile known for its remote wilderness and Patagonian landscapes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Arauco
Triple: [Biobío Region, containsCity, Arauco]
Generated description
Arauco is a coastal city and commune in Chile known for its forestry industry and location within the Biobío Region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Arauco
Target entity description: Arauco is a coastal city and commune in Chile known for its forestry industry and location within the Biobío Region.
  • A. Andacollo
    Andacollo is a small mining town and municipality in Chile’s Coquimbo Region, known for its copper deposits and the religious shrine of the Virgin of Andacollo.
  • B. Talcahuano
    Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
  • C. Pudahuel
    Pudahuel is a commune in the Santiago Metropolitan Region of Chile, known for hosting the country’s main international airport and forming part of the greater Santiago urban area.
  • D. Quirihue
    Quirihue is a small city in central Chile that serves as the capital of the Itata Province in the Ñuble Region.
  • E. Aysén Region
    The Aysén Region is a sparsely populated, fjord-filled and mountainous administrative region in southern Chile known for its remote wilderness and Patagonian landscapes.
  • F. None of above. chosen

Provenance (5 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_69a4938bdd3c8190a954a3c11844d9cf completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac22de288190913714d41e5a8e12 completed March 1, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c71702fc8190a143fe45b228ae24 completed March 4, 2026, 5:45 a.m.
NEDg Description generation batch_69a7ca67dbc88190b40fd74ad91a4bd6 completed March 4, 2026, 6 a.m.
NED2 Entity disambiguation (via description) batch_69a7cb0b497c8190926fce5cc5e99734 completed March 4, 2026, 6:02 a.m.
Created at: March 1, 2026, 7:38 p.m.