Triple

T17992552
Position Surface form Disambiguated ID Type / Status
Subject Madona Municipality E430411 entity
Predicate contains P35 FINISHED
Object Ērgļi
Ērgļi is a small town in central Latvia known for its scenic hilly landscape and forests within the Vidzeme region.
E1300470 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: Ērgļi | Statement: [Madona Municipality, contains, Ērgļi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ērgļi
Context triple: [Madona Municipality, contains, Ērgļi]
  • A. Zemgale
    Zemgale is a historical and cultural region in southern Latvia, known for its fertile plains and agricultural significance.
  • B. Saldus
    Saldus is a small town in western Latvia known for its regional cultural life and as a local economic and administrative center.
  • C. Latgale
    Latgale is a culturally distinct historical region in eastern Latvia, known for its lakes, rolling landscapes, and strong Latgalian linguistic and Catholic traditions.
  • D. Vianen
    Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
  • E. Balta
    Balta is a city that gained historical significance as a strategic location captured during the Uman–Botoșani offensive in World War II.
  • 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: Ērgļi
Triple: [Madona Municipality, contains, Ērgļi]
Generated description
Ērgļi is a small town in central Latvia known for its scenic hilly landscape and forests within the Vidzeme region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ērgļi
Target entity description: Ērgļi is a small town in central Latvia known for its scenic hilly landscape and forests within the Vidzeme region.
  • A. Zemgale
    Zemgale is a historical and cultural region in southern Latvia, known for its fertile plains and agricultural significance.
  • B. Saldus
    Saldus is a small town in western Latvia known for its regional cultural life and as a local economic and administrative center.
  • C. Latgale
    Latgale is a culturally distinct historical region in eastern Latvia, known for its lakes, rolling landscapes, and strong Latgalian linguistic and Catholic traditions.
  • D. Vianen
    Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
  • E. Balta
    Balta is a city that gained historical significance as a strategic location captured during the Uman–Botoșani offensive in World War II.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b2a0f8588190b6090c7cce60a35f completed April 19, 2026, 10:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0337ae62588190b1a6464fb703cc8f completed May 12, 2026, 2:22 p.m.
NEDg Description generation batch_6a033ca6a2608190a391694153070cc8 completed May 12, 2026, 2:43 p.m.
NED2 Entity disambiguation (via description) batch_6a033d6bf3f48190ac141febc04608f6 completed May 12, 2026, 2:47 p.m.
Created at: April 10, 2026, 10:23 a.m.