Triple

T6846794
Position Surface form Disambiguated ID Type / Status
Subject Gökçeada E157915 entity
Predicate hasSettlement P1068 FINISHED
Object Tepeköy E601890 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: Tepeköy | Statement: [Gökçeada, hasSettlement, Tepeköy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tepeköy
Context triple: [Gökçeada, hasSettlement, Tepeköy]
  • A. Tepeköy chosen
    Tepeköy is a village on the island of İmroz (Gökçeada) in Turkey, known for its traditional Greek heritage and rural Aegean character.
  • B. Boğazköy
    Boğazköy is an important archaeological site in central Turkey best known as the location of Hattusa, the former capital of the Hittite Empire.
  • C. Kartepe
    Kartepe is a district and popular winter sports and nature tourism destination located in Turkey’s Kocaeli Province, near the Marmara region.
  • D. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • E. Toprakkale
    Toprakkale is an ancient fortress and archaeological site in eastern Turkey that served as a significant center of the Iron Age Kingdom of Urartu.
  • 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_69c6882ed4c081909dc465a7cf8838be completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d7cd0e64819097c9c211df8bce54 completed March 27, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7427825d881909f151ca2ce3bd546 completed March 28, 2026, 2:52 a.m.
Created at: March 27, 2026, 2:20 p.m.