Triple

T12128815
Position Surface form Disambiguated ID Type / Status
Subject Mersin Province E288878 entity
Predicate contains P35 FINISHED
Object Erdemli E1028143 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: Erdemli | Statement: [Mersin Province, contains, Erdemli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erdemli
Context triple: [Mersin Province, contains, Erdemli]
  • A. Erdemli chosen
    Erdemli is a coastal district and town in southern Turkey known for its Mediterranean beaches, citrus production, and nearby ancient ruins.
  • B. Gümüldür
    Gümüldür is a coastal neighborhood and popular seaside resort area in the Menderes district of İzmir Province, Turkey.
  • C. Bilecik
    Bilecik is a small city in northwestern Turkey known as the capital of Bilecik Province and for its proximity to the historic town of Söğüt, birthplace of the Ottoman Empire.
  • D. Ereğli
    Ereğli is a district and town in central Turkey known for its agricultural production and location within Konya Province on the Central Anatolian plateau.
  • E. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158a2c2c8190aaff9d0cce177565 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f716afa8008190b4c518dd6004d87a completed May 3, 2026, 9:34 a.m.
Created at: April 8, 2026, 9:49 p.m.