Triple

T14625749
Position Surface form Disambiguated ID Type / Status
Subject Arga River E343339 entity
Predicate flowsThrough P225 FINISHED
Object Milagro E250930 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: Milagro | Statement: [Arga River, flowsThrough, Milagro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milagro
Context triple: [Arga River, flowsThrough, Milagro]
  • A. Milagro chosen
    Milagro is a city in Ecuador known as an important agricultural and commercial center, particularly for sugarcane and rice production.
  • B. Milagros
    Milagros is a coastal municipality in the province of Masbate in the Philippines, known for its fishing communities and rural agricultural economy.
  • C. Brazo Blest
    Brazo Blest is a scenic western arm of Nahuel Huapi Lake in Argentine Patagonia, known for its lush forests, waterfalls, and access to the Andes near the Chilean border.
  • D. Medalla Milagrosa
    Medalla Milagrosa is a station on the Buenos Aires Underground, located in the city’s southeastern area and serving the Line E route.
  • E. La Joya
    La Joya is the nickname of Argentine footballer Paulo Dybala, highlighting his status as a highly skilled and valuable attacking player.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb46a4a9081908472b0a542028a7f completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda92a6b9c8190bdb220444cfbe34a completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:26 a.m.