Triple

T11978438
Position Surface form Disambiguated ID Type / Status
Subject Western Anatolia E285093 entity
Predicate hasUniversityCity P4747 FINISHED
Object Denizli E335876 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: Denizli | Statement: [Western Anatolia, hasUniversityCity, Denizli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denizli
Context triple: [Western Anatolia, hasUniversityCity, Denizli]
  • A. Denizli chosen
    Denizli is a major industrial and commercial city in western Turkey, known for its textile production and proximity to the famous Pamukkale travertine terraces.
  • B. Gazipaşa
    Gazipaşa is a coastal town and district in Antalya Province, southern Turkey, known for its Mediterranean beaches, agricultural production, and proximity to ancient ruins.
  • C. Izmir
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • D. Çatalca
    Çatalca is a rural district on the western outskirts of Istanbul, known for its forests, farmland, and historical fortifications forming part of the city’s traditional land defenses.
  • E. Ayvacık
    Ayvacık is a small town and district in Turkey’s Çanakkale Province, known for its traditional stone houses and proximity to the Aegean coast and ancient sites like Assos.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90393cfb08190b5b45d3e5e32fad3 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e391d7c8190a414cb3306bfe139 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:46 p.m.