Triple

T17524714
Position Surface form Disambiguated ID Type / Status
Subject Bua E426764 entity
Predicate hasSettlement P1068 FINISHED
Object Dama
Dama is a settlement associated with the locality of Bua, likely a small village or community within its administrative area.
 E1274042 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: Dama | Statement: [Bua, hasSettlement, Dama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dama
Context triple: [Bua, hasSettlement, Dama]
  • A. Dama dama
    Dama dama, commonly known as the fallow deer, is a medium-sized deer species native to Europe and widely introduced elsewhere, recognized for its spotted coat and palmate antlers in males.
  • B. Kráľová dam
    Kráľová dam is a major hydroelectric and water-management reservoir on the Váh River in Slovakia, used for power generation, flood control, and irrigation.
  • C. Fiez
    Fiez is a small municipality in the canton of Vaud in western Switzerland, situated in the Jura-Nord vaudois district.
  • D. Raissa
    Raissa is a feminine given name of Russian origin, commonly used in Slavic countries.
  • E. Rook
    Rook is an open-source cloud-native storage orchestrator for Kubernetes that automates the deployment, management, and scaling of storage systems.
  • 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: Dama
Triple: [Bua, hasSettlement, Dama]
Generated description
Dama is a settlement associated with the locality of Bua, likely a small village or community within its administrative area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dama
Target entity description: Dama is a settlement associated with the locality of Bua, likely a small village or community within its administrative area.
  • A. Dama dama
    Dama dama, commonly known as the fallow deer, is a medium-sized deer species native to Europe and widely introduced elsewhere, recognized for its spotted coat and palmate antlers in males.
  • B. Kráľová dam
    Kráľová dam is a major hydroelectric and water-management reservoir on the Váh River in Slovakia, used for power generation, flood control, and irrigation.
  • C. Fiez
    Fiez is a small municipality in the canton of Vaud in western Switzerland, situated in the Jura-Nord vaudois district.
  • D. Raissa
    Raissa is a feminine given name of Russian origin, commonly used in Slavic countries.
  • E. Rook
    Rook is an open-source cloud-native storage orchestrator for Kubernetes that automates the deployment, management, and scaling of storage systems.
  • 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d592a081909bf876d606158b2d completed April 19, 2026, 3:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01c9473100819081079a0db51391cc completed May 11, 2026, 12:19 p.m.
NEDg Description generation batch_6a01cb2016f8819090e8ec20428cfdaf completed May 11, 2026, 12:27 p.m.
NED2 Entity disambiguation (via description) batch_6a01cbad7bf481909c754049686c5b39 completed May 11, 2026, 12:29 p.m.
Created at: April 10, 2026, 5:49 a.m.