Triple

T11736811
Position Surface form Disambiguated ID Type / Status
Subject Samsun Province E279047 entity
Predicate hasDistrict P459 FINISHED
Object Havza
Havza is a district and town in northern Turkey known for its thermal springs and location within Samsun Province in the Black Sea region.
E952737 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: Havza | Statement: [Samsun Province, hasDistrict, Havza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Havza
Context triple: [Samsun Province, hasDistrict, Havza]
  • A. Gürsu
    Gürsu is a district and rapidly developing urban area located within Turkey’s northwestern Bursa Province.
  • B. Beyşehir
    Beyşehir is a town and district in central Turkey known for its large freshwater lake, Lake Beyşehir, and its rich Seljuk-era architectural heritage.
  • C. Yassıada
    Yassıada is one of Istanbul’s Princes' Islands in the Sea of Marmara, historically known for its use as a place of exile and for hosting the 1960–61 trials of Turkish political leaders.
  • D. Yakapınar
    Yakapınar is a modern settlement in southern Turkey located near the site of the ancient city of Mopsuestia.
  • E. Darıca
    Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
  • 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: Havza
Triple: [Samsun Province, hasDistrict, Havza]
Generated description
Havza is a district and town in northern Turkey known for its thermal springs and location within Samsun Province in the Black Sea region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Havza
Target entity description: Havza is a district and town in northern Turkey known for its thermal springs and location within Samsun Province in the Black Sea region.
  • A. Gürsu
    Gürsu is a district and rapidly developing urban area located within Turkey’s northwestern Bursa Province.
  • B. Beyşehir
    Beyşehir is a town and district in central Turkey known for its large freshwater lake, Lake Beyşehir, and its rich Seljuk-era architectural heritage.
  • C. Yassıada
    Yassıada is one of Istanbul’s Princes' Islands in the Sea of Marmara, historically known for its use as a place of exile and for hosting the 1960–61 trials of Turkish political leaders.
  • D. Yakapınar
    Yakapınar is a modern settlement in southern Turkey located near the site of the ancient city of Mopsuestia.
  • E. Darıca
    Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4edced48190b7a59dd45921828e completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4174972ac819094f3938b18a5081e completed May 1, 2026, 3 a.m.
NEDg Description generation batch_69f41f16f43c81909f5d36e8b4b0b9c3 completed May 1, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f4225a4b5c8190958aaddbd10035b1 completed May 1, 2026, 3:47 a.m.
Created at: April 8, 2026, 9:41 p.m.