Triple

T21372300
Position Surface form Disambiguated ID Type / Status
Subject Geldern E527096 entity
Predicate hasTwinTown P919 FINISHED
Object Pontaumur 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: Pontaumur | Statement: [Geldern, hasTwinTown, Pontaumur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pontaumur
Context triple: [Geldern, hasTwinTown, Pontaumur]
  • A. Pontaumur chosen
    Pontaumur is a small commune in central France, known for its rural setting in the Puy-de-Dôme department of the Auvergne region.
  • B. Ponta
    Ponta is a Romanian surname most notably borne by Victor Ponta, a former Prime Minister of Romania.
  • C. Ponta Baleia
    Ponta Baleia is a small coastal settlement on the southern tip of São Tomé Island in São Tomé and Príncipe, known primarily as the mainland departure point for boats to Ilhéu das Rolas.
  • D. La Punta
    La Punta is a planned city in central Argentina known for its rapid development and modern infrastructure within San Luis Province.
  • E. La Punta
    La Punta is a small coastal district of the Constitutional Province of Callao in Peru, known for its beaches, historic architecture, and naval and port-related activities.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0b0d5ec81908da8f38380dbdc7a completed April 22, 2026, 11:27 a.m.
Created at: April 16, 2026, 5:10 p.m.