Triple

T9421989
Position Surface form Disambiguated ID Type / Status
Subject Masaesyli E227174 entity
Predicate capital P234 FINISHED
Object Siga
Siga was an ancient North African city that served as the political and economic center of the Masaesyli kingdom in Numidia.
 E798457 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: Siga | Statement: [Masaesyli, capital, Siga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Siga
Context triple: [Masaesyli, capital, Siga]
  • A. Siasi
    Siasi is an island municipality in the southern Philippines known for its predominantly Muslim population, fishing-based economy, and location within the Sulu Sea.
  • B. Sikma
    Sikma is a surname most notably associated with Jack Sikma, a Hall of Fame American basketball player known for his successful NBA career with the Seattle SuperSonics.
  • C. Siatista
    Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
  • D. Siguiri
    Siguiri is a town in northeastern Guinea known as a center of gold mining along the Niger River.
  • E. Solita
    Solita is a small municipality located in the Caquetá Department of southern Colombia, known for its rural character within the Amazonian foothills region.
  • 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: Siga
Triple: [Masaesyli, capital, Siga]
Generated description
Siga was an ancient North African city that served as the political and economic center of the Masaesyli kingdom in Numidia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Siga
Target entity description: Siga was an ancient North African city that served as the political and economic center of the Masaesyli kingdom in Numidia.
  • A. Siasi
    Siasi is an island municipality in the southern Philippines known for its predominantly Muslim population, fishing-based economy, and location within the Sulu Sea.
  • B. Sikma
    Sikma is a surname most notably associated with Jack Sikma, a Hall of Fame American basketball player known for his successful NBA career with the Seattle SuperSonics.
  • C. Siatista
    Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
  • D. Siguiri
    Siguiri is a town in northeastern Guinea known as a center of gold mining along the Niger River.
  • E. Solita
    Solita is a small municipality located in the Caquetá Department of southern Colombia, known for its rural character within the Amazonian foothills region.
  • 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_69ca8436ba308190903e470776d2d893 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd6c2651c48190808281779fab49df completed April 1, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107d290148190855b8d50eb80c591 completed April 4, 2026, 12:45 p.m.
NEDg Description generation batch_69d108d87adc8190b602c115c09650d6 completed April 4, 2026, 12:49 p.m.
NED2 Entity disambiguation (via description) batch_69d10995e3bc8190a8db18e4ed0fc261 completed April 4, 2026, 12:52 p.m.
Created at: March 30, 2026, 7:48 p.m.