Triple

T1384871
Position Surface form Disambiguated ID Type / Status
Subject Sumba E29821 entity
Predicate hasLargestCity P235 FINISHED
Object Waingapu
Waingapu is the main urban and economic center of the Indonesian island of Sumba, serving as a key hub for transportation and regional administration.
 E157751 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: Waingapu | Statement: [Sumba, hasLargestCity, Waingapu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Waingapu
Context triple: [Sumba, hasLargestCity, Waingapu]
  • A. Urunga
    Urunga is a small coastal town in New South Wales, Australia, known for its scenic boardwalks, estuary views, and relaxed seaside atmosphere.
  • B. Sukoró
    Sukoró is a village in Hungary’s Fejér County, known as a lakeside resort and recreational area on the northern shore of Lake Velence.
  • C. Tamba
    Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
  • D. Yenda
    Yenda is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural production, particularly viticulture and horticulture.
  • E. Sumba
    Sumba is a rugged island in eastern Indonesia known for its traditional Marapu culture, megalithic tombs, and distinctive ikat textiles.
  • 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: Waingapu
Triple: [Sumba, hasLargestCity, Waingapu]
Generated description
Waingapu is the main urban and economic center of the Indonesian island of Sumba, serving as a key hub for transportation and regional administration.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Waingapu
Target entity description: Waingapu is the main urban and economic center of the Indonesian island of Sumba, serving as a key hub for transportation and regional administration.
  • A. Urunga
    Urunga is a small coastal town in New South Wales, Australia, known for its scenic boardwalks, estuary views, and relaxed seaside atmosphere.
  • B. Sukoró
    Sukoró is a village in Hungary’s Fejér County, known as a lakeside resort and recreational area on the northern shore of Lake Velence.
  • C. Tamba
    Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
  • D. Yenda
    Yenda is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural production, particularly viticulture and horticulture.
  • E. Sumba
    Sumba is a rugged island in eastern Indonesia known for its traditional Marapu culture, megalithic tombs, and distinctive ikat textiles.
  • 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_69a498dc92f8819094a1108f8ac90f43 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c33896548190b44f70c9aaaed9b6 completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd48e046c8190bc4820d6c4ce907d completed March 8, 2026, 1:44 a.m.
NEDg Description generation batch_69acd57bf87c8190ad22de7b5636fcfc completed March 8, 2026, 1:48 a.m.
NED2 Entity disambiguation (via description) batch_69acd5e54e98819084ba0022ca64ff43 completed March 8, 2026, 1:50 a.m.
Created at: March 1, 2026, 7:59 p.m.