Triple

T20568029
Position Surface form Disambiguated ID Type / Status
Subject Nusantara Building E505013 entity
Predicate locatedIn P40 FINISHED
Object Senayan
Senayan is a central district in Jakarta, Indonesia, known for its major government buildings, sports complexes, and commercial centers.
E1438351 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: Senayan | Statement: [Nusantara Building, locatedIn, Senayan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Senayan
Context triple: [Nusantara Building, locatedIn, Senayan]
  • A. Balai Besar
    Balai Besar is a historic royal audience hall and ceremonial building located in Alor Setar, Kedah, Malaysia.
  • B. Taman Ujung
    Taman Ujung is a historic water palace and scenic royal garden complex in eastern Bali, Indonesia, known for its ornate pools, pavilions, and ocean views.
  • C. Taman Kosas
    Taman Kosas is a residential township located within the municipality of Ampang Jaya in Selangor, Malaysia.
  • D. Sepilok
    Sepilok is a forested area in Sabah, Malaysian Borneo, best known for its wildlife reserves and as a major ecotourism destination focused on orangutan conservation.
  • E. Taman
    Taman is a Nilo-Saharan language spoken by the Taman people in parts of Chad and Sudan.
  • 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: Senayan
Triple: [Nusantara Building, locatedIn, Senayan]
Generated description
Senayan is a central district in Jakarta, Indonesia, known for its major government buildings, sports complexes, and commercial centers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Senayan
Target entity description: Senayan is a central district in Jakarta, Indonesia, known for its major government buildings, sports complexes, and commercial centers.
  • A. Balai Besar
    Balai Besar is a historic royal audience hall and ceremonial building located in Alor Setar, Kedah, Malaysia.
  • B. Taman Ujung
    Taman Ujung is a historic water palace and scenic royal garden complex in eastern Bali, Indonesia, known for its ornate pools, pavilions, and ocean views.
  • C. Taman Kosas
    Taman Kosas is a residential township located within the municipality of Ampang Jaya in Selangor, Malaysia.
  • D. Sepilok
    Sepilok is a forested area in Sabah, Malaysian Borneo, best known for its wildlife reserves and as a major ecotourism destination focused on orangutan conservation.
  • E. Taman
    Taman is a Nilo-Saharan language spoken by the Taman people in parts of Chad and Sudan.
  • 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_69e0b4b6587c8190aee63dc7cff244ea completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a7a3fdc08190a34dcf4c4e51f078 completed April 20, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08acdffa2c8190a87c367eb068e2cf completed May 16, 2026, 5:44 p.m.
NEDg Description generation batch_6a08ad96b2a081908d32e335c5265eec completed May 16, 2026, 5:47 p.m.
NED2 Entity disambiguation (via description) batch_6a08ae19eca08190ada48b48105be62d completed May 16, 2026, 5:49 p.m.
Created at: April 16, 2026, 11:39 a.m.