Triple

T3276537
Position Surface form Disambiguated ID Type / Status
Subject Taurus Mountains E68770 entity
Predicate nearbyCity P350 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: [Taurus Mountains, nearbyCity, Mersin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mersin
Context triple: [Taurus Mountains, nearbyCity, Mersin]
  • A. Antakya
    Antakya is a city in southern Turkey, historically known as Antioch, renowned as an important center of Hellenistic, Roman, and early Christian civilization.
  • B. 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.
  • C. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • D. Gaziantep
    Gaziantep is a major city in southeastern Turkey known for its rich history, cultural heritage, and renowned pistachio-based cuisine, especially baklava.
  • E. Antalya
    Antalya is a major resort city on Turkey’s Mediterranean coast, known for its beaches, historic old town, and role as a gateway to the Turkish Riviera.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0128f08819084644f3c8fda2596 completed March 8, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a698ab08190b558c4ff3f9b27fc completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:10 p.m.