Triple

T13721836
Position Surface form Disambiguated ID Type / Status
Subject Southern Spain E329055 entity
Predicate hasCity P316 FINISHED
Object Ronda E217795 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: Ronda | Statement: [Southern Spain, hasCity, Ronda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ronda
Context triple: [Southern Spain, hasCity, Ronda]
  • A. Ronda chosen
    Ronda is a historic mountaintop city in Spain’s Málaga province, famed for its dramatic gorge-spanning bridges, whitewashed old town, and deep cultural ties to bullfighting and Spanish military tradition.
  • B. Ronda
    Ronda is a coastal municipality in the province of Cebu in the Philippines, known for its rural communities and agricultural landscape.
  • C. Nerja
    Nerja is a coastal town on Spain’s Costa del Sol, known for its beaches, dramatic cliffs, and the famous Nerja Caves.
  • D. Aracena
    Aracena is a historic town in southwestern Spain renowned for its medieval castle and the Gruta de las Maravillas cave system.
  • E. Vacqueyras
    Vacqueyras is a renowned southern Rhône wine appellation in France known for its robust red wines primarily based on Grenache, Syrah, and Mourvèdre.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69de01f3b46481909ceedfa78e9ca92b completed April 14, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7a84a2ed481909005720b0531e585 completed May 3, 2026, 7:55 p.m.
Created at: April 9, 2026, 9:55 p.m.