Triple

T10043720
Position Surface form Disambiguated ID Type / Status
Subject Aruwimi River E205357 entity
Predicate hasSettlementOnBank P1010 FINISHED
Object Buta
Buta is a town in the northern Democratic Republic of the Congo that serves as an administrative and commercial center in the Aruwimi River region.
 E838538 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: Buta | Statement: [Aruwimi River, hasSettlementOnBank, Buta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Buta
Context triple: [Aruwimi River, hasSettlementOnBank, Buta]
  • A. Boso
    Boso is the fictional dialogue partner and student of Anselm of Canterbury in the theological treatise "Cur Deus Homo," representing the questioning layperson in discussions about the Incarnation and Atonement.
  • B. Ushi
    Ushi is the affectionate nickname of Japanese professional football club Vissel Kobe, reflecting its local identity and fan culture.
  • C. Saru
    Saru is a Kelpien Starfleet officer in Star Trek: Discovery, known for his cautious nature, strong moral compass, and eventual rise to command.
  • D. Bachué
    Bachué is a principal mother goddess in Muisca mythology, associated with creation, fertility, and the origin of humanity.
  • E. Kodo
    Kodo is the main lecture and assembly hall of the historic Yakushi-ji Buddhist temple in Nara, Japan.
  • 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: Buta
Triple: [Aruwimi River, hasSettlementOnBank, Buta]
Generated description
Buta is a town in the northern Democratic Republic of the Congo that serves as an administrative and commercial center in the Aruwimi River region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Buta
Target entity description: Buta is a town in the northern Democratic Republic of the Congo that serves as an administrative and commercial center in the Aruwimi River region.
  • A. Boso
    Boso is the fictional dialogue partner and student of Anselm of Canterbury in the theological treatise "Cur Deus Homo," representing the questioning layperson in discussions about the Incarnation and Atonement.
  • B. Ushi
    Ushi is the affectionate nickname of Japanese professional football club Vissel Kobe, reflecting its local identity and fan culture.
  • C. Saru
    Saru is a Kelpien Starfleet officer in Star Trek: Discovery, known for his cautious nature, strong moral compass, and eventual rise to command.
  • D. Bachué
    Bachué is a principal mother goddess in Muisca mythology, associated with creation, fertility, and the origin of humanity.
  • E. Kodo
    Kodo is the main lecture and assembly hall of the historic Yakushi-ji Buddhist temple in Nara, Japan.
  • 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf61b3e08190b69bcf67b6a95342 completed April 2, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a35fbc081908ec7d359ec3332f2 completed April 5, 2026, 5:21 p.m.
NEDg Description generation batch_69d29b7430248190b8965eaf1286dd7c completed April 5, 2026, 5:27 p.m.
NED2 Entity disambiguation (via description) batch_69d29c7ba9f081908f4614098d6c954b completed April 5, 2026, 5:31 p.m.
Created at: March 30, 2026, 8:55 p.m.