Triple

T11736810
Position Surface form Disambiguated ID Type / Status
Subject Samsun Province E279047 entity
Predicate hasDistrict P459 FINISHED
Object Terme
Terme is a coastal district and town in Turkey’s Black Sea region, located within Samsun Province and known for its agriculture and riverine landscape.
 E944355 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: Terme | Statement: [Samsun Province, hasDistrict, Terme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Terme
Context triple: [Samsun Province, hasDistrict, Terme]
  • A. Telese Terme
    Telese Terme is a spa town in the Campania region of southern Italy, known for its thermal baths and mineral springs.
  • B. Temerin
    Temerin is a town and municipality in the autonomous province of Vojvodina in northern Serbia.
  • C. Talfer
    The Talfer is a river in South Tyrol, northern Italy, that flows through the city of Bolzano as a tributary of the Adige.
  • D. Tarusa
    Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
  • E. Palten
    Palten is a river in Austria that serves as a significant tributary of the Enns River in the Styrian region.
  • 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: Terme
Triple: [Samsun Province, hasDistrict, Terme]
Generated description
Terme is a coastal district and town in Turkey’s Black Sea region, located within Samsun Province and known for its agriculture and riverine landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Terme
Target entity description: Terme is a coastal district and town in Turkey’s Black Sea region, located within Samsun Province and known for its agriculture and riverine landscape.
  • A. Telese Terme
    Telese Terme is a spa town in the Campania region of southern Italy, known for its thermal baths and mineral springs.
  • B. Temerin
    Temerin is a town and municipality in the autonomous province of Vojvodina in northern Serbia.
  • C. Talfer
    The Talfer is a river in South Tyrol, northern Italy, that flows through the city of Bolzano as a tributary of the Adige.
  • D. Tarusa
    Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
  • E. Palten
    Palten is a river in Austria that serves as a significant tributary of the Enns River in the Styrian region.
  • 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_69f019b318188190bfb7effcf42974d2 completed April 28, 2026, 2:21 a.m.
NEDg Description generation batch_69f0319271788190a105828ae7582668 completed April 28, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_69f05aa351888190a31092e6a9aee26b completed April 28, 2026, 6:58 a.m.
Created at: April 8, 2026, 9:41 p.m.