Triple

T7255722
Position Surface form Disambiguated ID Type / Status
Subject Black Sea coast E157716 entity
Predicate hasCity P316 FINISHED
Object Giresun
Giresun is a coastal city in northeastern Turkey known for its hazelnut production and scenic location along the Black Sea.
 E656516 NE FINISHED

How this triple was built (4 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: Giresun | Statement: [Black Sea coast, hasCity, Giresun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Giresun
Context triple: [Black Sea coast, hasCity, Giresun]
  • A. Kırklareli
    Kırklareli is a city in northwestern Turkey known for its location near the Bulgarian border, agricultural economy, and historical Ottoman-era architecture.
  • B. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • C. Izmit
    Izmit is an industrial and port city in northwestern Turkey, located east of Istanbul along the Gulf of Izmit.
  • D. Denizli
    Denizli is a major industrial and commercial city in western Turkey, known for its textile production and proximity to the famous Pamukkale travertine terraces.
  • E. Ardahan
    Ardahan is a town in northeastern Turkey that serves as the capital of Ardahan Province near the border with Georgia.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Giresun
Triple: [Black Sea coast, hasCity, Giresun]
Generated description
Giresun is a coastal city in northeastern Turkey known for its hazelnut production and scenic location along the Black Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Giresun
Target entity description: Giresun is a coastal city in northeastern Turkey known for its hazelnut production and scenic location along the Black Sea.
  • A. Kırklareli
    Kırklareli is a city in northwestern Turkey known for its location near the Bulgarian border, agricultural economy, and historical Ottoman-era architecture.
  • B. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • C. Izmit
    Izmit is an industrial and port city in northwestern Turkey, located east of Istanbul along the Gulf of Izmit.
  • D. Denizli
    Denizli is a major industrial and commercial city in western Turkey, known for its textile production and proximity to the famous Pamukkale travertine terraces.
  • E. Ardahan
    Ardahan is a town in northeastern Turkey that serves as the capital of Ardahan Province near the border with Georgia.
  • F. None of above. chosen

Provenance (5 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_69c6882d81d4819085f7ff862951ee4f completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6eaa0c76c81909fe43ed6938a13ea completed March 27, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eed1b5a48190875e9e0bfdc80ae4 completed March 28, 2026, 3:08 p.m.
NEDg Description generation batch_69c7efa4f5148190842f30988cbea94c completed March 28, 2026, 3:11 p.m.
NED2 Entity disambiguation (via description) batch_69c7f0092bac819080ded1863f99290a completed March 28, 2026, 3:13 p.m.
Created at: March 27, 2026, 2:56 p.m.