Triple

T16106639
Position Surface form Disambiguated ID Type / Status
Subject Levantine Sea E390753 entity
Predicate hasMajorPort P942 FINISHED
Object Mersin E288878 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: Mersin | Statement: [Levantine Sea, hasMajorPort, Mersin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mersin
Context triple: [Levantine Sea, hasMajorPort, Mersin]
  • A. Mecidiye
    Mecidiye is the former Ottoman-era name of the Romanian city now known as Medgidia, located in the Dobruja region.
  • B. Antakya
    Antakya is a city in southern Turkey, historically known as Antioch, renowned as an important center of Hellenistic, Roman, and early Christian civilization.
  • C. Mersin Province chosen
    Mersin Province is a coastal region in southern Turkey on the Mediterranean Sea, known for its major port city of Mersin and its rich historical and agricultural significance.
  • D. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • E. Burdur
    Burdur is a city in southwestern Turkey known for its nearby lakes, archaeological sites, and traditional Ottoman-era architecture.
  • 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6d81d081909e1315f4dbfd7369 completed April 17, 2026, 9:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff2a16acc8190be9ed181c7a44def completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 5 a.m.