Triple

T13143944
Position Surface form Disambiguated ID Type / Status
Subject Biotrén E312286 entity
Predicate connects P390 FINISHED
Object Talcahuano and Hualqui E74676 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: Talcahuano and Hualqui | Statement: [Biotrén, connects, Talcahuano and Hualqui]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Talcahuano and Hualqui
Context triple: [Biotrén, connects, Talcahuano and Hualqui]
  • A. Talcahuano chosen
    Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
  • B. Talca
    Talca is a major city in central Chile known as an administrative, commercial, and agricultural hub in the Maule Valley.
  • C. Quillota
    Quillota is a Chilean city known for its agricultural production and historical significance within the Valparaíso Region.
  • D. Rancagua
    Rancagua is a major Chilean city known for its mining industry and historical significance in the country’s independence, serving as an important commercial and administrative center south of Santiago.
  • E. Nancagua
    Nancagua is a town and commune in central Chile’s Colchagua Valley, known for its agricultural activity and wine production.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bce3678819082a7aa1d83f20592 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5d809948190aced5ce377402463 completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 9:10 p.m.