Triple

T14059563
Position Surface form Disambiguated ID Type / Status
Subject Ursula von Rydingsvard E338307 entity
Predicate notableWork P4 FINISHED
Object Luba
Luba is a monumental wooden sculpture by artist Ursula von Rydingsvard, exemplifying her signature hand-carved, architectonic style.
 E1078661 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: Luba | Statement: [Ursula von Rydingsvard, notableWork, Luba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luba
Context triple: [Ursula von Rydingsvard, notableWork, Luba]
  • A. Luba
    Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
  • B. Luba
    The Luba are a major Bantu-speaking ethnic group of Central Africa, historically known for the powerful Luba Kingdom centered in what is now the Democratic Republic of the Congo.
  • C. Lunda
    Lunda is a Bantu language spoken primarily by the Lunda people in parts of Zambia, Angola, and the Democratic Republic of the Congo.
  • D. Nkoya
    Nkoya is a Bantu language spoken primarily in western Zambia by the Nkoya people.
  • E. Lubemba
    Lubemba is the traditional kingdom and cultural heartland of the Bemba people in what is now northern Zambia.
  • 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: Luba
Triple: [Ursula von Rydingsvard, notableWork, Luba]
Generated description
Luba is a monumental wooden sculpture by artist Ursula von Rydingsvard, exemplifying her signature hand-carved, architectonic style.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luba
Target entity description: Luba is a monumental wooden sculpture by artist Ursula von Rydingsvard, exemplifying her signature hand-carved, architectonic style.
  • A. Luba
    Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
  • B. Luba
    The Luba are a major Bantu-speaking ethnic group of Central Africa, historically known for the powerful Luba Kingdom centered in what is now the Democratic Republic of the Congo.
  • C. Lunda
    Lunda is a Bantu language spoken primarily by the Lunda people in parts of Zambia, Angola, and the Democratic Republic of the Congo.
  • D. Nkoya
    Nkoya is a Bantu language spoken primarily in western Zambia by the Nkoya people.
  • E. Lubemba
    Lubemba is the traditional kingdom and cultural heartland of the Bemba people in what is now northern Zambia.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5686f51c81908c33143ecbaae83d completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb662c37c8190a629278a97060080 completed May 7, 2026, 3:57 p.m.
NEDg Description generation batch_69fcc99fca8c8190bbcafba5bacfdfda completed May 7, 2026, 5:19 p.m.
NED2 Entity disambiguation (via description) batch_69fcca3a375c819092b3f67612d2ec0c completed May 7, 2026, 5:22 p.m.
Created at: April 9, 2026, 10:21 p.m.