Triple

T7374270
Position Surface form Disambiguated ID Type / Status
Subject Maracaibo E170084 entity
Predicate locatedBy P2409 FINISHED
Object Lake Maracaibo E166855 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: Lake Maracaibo | Statement: [Maracaibo, locatedBy, Lake Maracaibo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Maracaibo
Context triple: [Maracaibo, locatedBy, Lake Maracaibo]
  • A. Lake Maracaibo chosen
    Lake Maracaibo is a large brackish bay in northwestern Venezuela, famous for its prolific oil fields and frequent lightning storms.
  • B. Bahía de Caráquez
    Bahía de Caráquez is a coastal city in western Ecuador known for its beaches, tourism, and location at the mouth of the Chone River on the Pacific Ocean.
  • C. Gulf of Paria
    The Gulf of Paria is a shallow, semi-enclosed inland sea of the Caribbean located between Venezuela and Trinidad, known for its rich fisheries and major shipping routes.
  • D. Gulf of Venezuela
    The Gulf of Venezuela is a shallow, strategically important inlet of the Caribbean Sea located between Venezuela and Colombia, serving as a key maritime route and connection to Lake Maracaibo’s oil-rich basin.
  • E. Ciénaga
    Ciénaga is a coastal municipality in northern Colombia known for its Caribbean beaches, historic architecture, and role in the country’s banana-growing region.
  • 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_69c68a5bfaac81909ce7f001dfb70c76 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1a6643c81909d626c8b6a7a11fd completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802ce8e408190946637d04083521c completed March 28, 2026, 4:33 p.m.
Created at: March 27, 2026, 3:07 p.m.