Triple

T4914167
Position Surface form Disambiguated ID Type / Status
Subject Korčula E110307 entity
Predicate hasSettlement P1068 FINISHED
Object Lumbarda
Lumbarda is a coastal village and popular tourist destination on the eastern tip of the Croatian island of Korčula, known for its sandy beaches and local wine production.
E478882 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: Lumbarda | Statement: [Korčula, hasSettlement, Lumbarda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lumbarda
Context triple: [Korčula, hasSettlement, Lumbarda]
  • A. Arogno
    Arogno is a small municipality in the canton of Ticino in southern Switzerland, located near Lake Lugano and the Italian border.
  • B. Tognana
    Tognana is a frazione (hamlet) of the municipality of Piove di Sacco in the Veneto region of northern Italy.
  • C. Ravanica
    Ravanica is a river in central Serbia that flows through the region before joining the Velika Morava.
  • D. Fussa
    Fussa is a city in western Tokyo, Japan, known for hosting Yokota Air Base and various Japan Air Self-Defense Force facilities.
  • E. Luga
    Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
  • 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: Lumbarda
Triple: [Korčula, hasSettlement, Lumbarda]
Generated description
Lumbarda is a coastal village and popular tourist destination on the eastern tip of the Croatian island of Korčula, known for its sandy beaches and local wine production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lumbarda
Target entity description: Lumbarda is a coastal village and popular tourist destination on the eastern tip of the Croatian island of Korčula, known for its sandy beaches and local wine production.
  • A. Arogno
    Arogno is a small municipality in the canton of Ticino in southern Switzerland, located near Lake Lugano and the Italian border.
  • B. Tognana
    Tognana is a frazione (hamlet) of the municipality of Piove di Sacco in the Veneto region of northern Italy.
  • C. Ravanica
    Ravanica is a river in central Serbia that flows through the region before joining the Velika Morava.
  • D. Fussa
    Fussa is a city in western Tokyo, Japan, known for hosting Yokota Air Base and various Japan Air Self-Defense Force facilities.
  • E. Luga
    Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
  • 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_69bd44132b94819088522d92beaadc78 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e9f12b48190b3cb5378958d03cd completed March 20, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6feaf3dc81908b2c7a7409b1c952 completed March 21, 2026, 10:16 a.m.
NEDg Description generation batch_69be7147bff8819097059b1b24e2b0f7 completed March 21, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_69be71d8dc6081908608d9e90498579b completed March 21, 2026, 10:24 a.m.
Created at: March 20, 2026, 1:29 p.m.