Triple

T12410833
Position Surface form Disambiguated ID Type / Status
Subject Nevşehir E296508 entity
Predicate hasNearbyAttraction P2064 FINISHED
Object Ürgüp E294549 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: Ürgüp | Statement: [Nevşehir, hasNearbyAttraction, Ürgüp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ürgüp
Context triple: [Nevşehir, hasNearbyAttraction, Ürgüp]
  • A. Ürgüp chosen
    Ürgüp is a historic town in Turkey’s Cappadocia region, known for its fairy-chimney rock formations, cave hotels, and wine production.
  • B. Gürün
    Gürün is a town and district in central Turkey known for its historical sites and distinctive natural landscapes within Sivas Province.
  • C. Gürbulak
    Gürbulak is a Turkish border village and crossing point on the frontier with Iran, serving as a key gateway between the two countries.
  • D. Gürsu
    Gürsu is a district and rapidly developing urban area located within Turkey’s northwestern Bursa Province.
  • E. Uğurlu
    Uğurlu is a village on the island of İmroz (Gökçeada) in the Aegean Sea, part of Turkey’s Çanakkale Province.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d4b86c88190afba0de15b34eee9 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ea44a808190af2c5a6633120814 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 9:55 p.m.