Triple

T18087129
Position Surface form Disambiguated ID Type / Status
Subject Rupanco Lake E432863 entity
Predicate hasNearbyTown P3883 FINISHED
Object Entre Lagos NE NERFINISHED

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: Entre Lagos | Statement: [Rupanco Lake, hasNearbyTown, Entre Lagos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Entre Lagos
Context triple: [Rupanco Lake, hasNearbyTown, Entre Lagos]
  • A. Entre Lagos chosen
    Entre Lagos is a small lakeside town in southern Chile known as a gateway to the Puyehue and Rupanco lake region and nearby Andean landscapes.
  • B. Omkara
    Omkara is a critically acclaimed 2006 Indian crime drama film directed by Vishal Bhardwaj, adapted from Shakespeare’s Othello and known for its intense performances and rustic Uttar Pradesh setting.
  • C. Ojo
    Ojo is a central character in L. Frank Baum’s Oz series, notably a Munchkin boy whose quest drives the plot of "The Patchwork Girl of Oz."
  • D. Ojo
    Ojo is a suburban local government area in Lagos State, Nigeria, known for its rapidly growing residential communities and the presence of institutions like Lagos State University.
  • E. Yaba
    Yaba is a bustling commercial and residential district on Lagos Mainland in Nigeria, known for its markets, educational institutions, and growing tech startup scene.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b907d05c819083cc3bd6021089e6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dd150ab88190864be2a722d214b8 completed April 19, 2026, 1:48 p.m.
Created at: April 10, 2026, 10:27 a.m.