Triple

T10489655
Position Surface form Disambiguated ID Type / Status
Subject Gambela Region E247380 entity
Predicate hasMajorTown P316 FINISHED
Object Itang
Itang is a town in western Ethiopia that serves as one of the principal urban centers of the Gambela Region.
 E867097 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: Itang | Statement: [Gambela Region, hasMajorTown, Itang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Itang
Context triple: [Gambela Region, hasMajorTown, Itang]
  • A. Sarangani
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • B. Ilonggo
    Ilonggo is a major Austronesian language spoken primarily in Western Visayas and parts of Mindanao in the Philippines.
  • C. Indang
    Indang is a landlocked agricultural municipality in the province of Cavite in the Philippines, known for its coffee, coconut, and relatively cool climate.
  • D. Sasmuan
    Sasmuan is a coastal municipality in the province of Pampanga in the Philippines, known for its fishing industry, wetlands, and bird-watching sites.
  • E. Isinay
    Isinay is an Austronesian language spoken by the Isinay people of northern Luzon in the Philippines, noted for its distinct phonology and grammar compared to neighboring Philippine languages.
  • 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: Itang
Triple: [Gambela Region, hasMajorTown, Itang]
Generated description
Itang is a town in western Ethiopia that serves as one of the principal urban centers of the Gambela Region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Itang
Target entity description: Itang is a town in western Ethiopia that serves as one of the principal urban centers of the Gambela Region.
  • A. Sarangani
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • B. Ilonggo
    Ilonggo is a major Austronesian language spoken primarily in Western Visayas and parts of Mindanao in the Philippines.
  • C. Indang
    Indang is a landlocked agricultural municipality in the province of Cavite in the Philippines, known for its coffee, coconut, and relatively cool climate.
  • D. Sasmuan
    Sasmuan is a coastal municipality in the province of Pampanga in the Philippines, known for its fishing industry, wetlands, and bird-watching sites.
  • E. Isinay
    Isinay is an Austronesian language spoken by the Isinay people of northern Luzon in the Philippines, noted for its distinct phonology and grammar compared to neighboring Philippine languages.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5097ca5c081908b47a08ca7885650 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc9792308190b09d6aaed63dd418 completed April 10, 2026, 11:18 a.m.
NEDg Description generation batch_69d8e8c81bdc8190b6b6dfe00025b514 completed April 10, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d901e1ecf88190acd24a0e20462cb9 completed April 10, 2026, 1:57 p.m.
Created at: April 6, 2026, 12:23 p.m.