Triple

T12386832
Position Surface form Disambiguated ID Type / Status
Subject Maitum E295887 entity
Predicate hasBarangay P29835 FINISHED
Object Kiambing
Kiambing is a barangay (village-level administrative division) of the municipality of Maitum in the province of Sarangani, Philippines.
 E979440 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: Kiambing | Statement: [Maitum, hasBarangay, Kiambing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kiambing
Context triple: [Maitum, hasBarangay, Kiambing]
  • A. Kabuna
    Kabuna is a small village located on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
  • B. Komo
    The Komo are an ethnic group indigenous to western Ethiopia, particularly associated with the Gambela Region, with their own distinct language and cultural traditions.
  • C. Dongo
    Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
  • D. Nasua
    Nasua is a genus of medium-sized, long-snouted mammals commonly known as coatis, native to the Americas and related to raccoons.
  • E. Kiamba
    Kiamba is a coastal municipality in the province of South Cotabato in the Philippines, known for its fishing industry and scenic natural attractions.
  • 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: Kiambing
Triple: [Maitum, hasBarangay, Kiambing]
Generated description
Kiambing is a barangay (village-level administrative division) of the municipality of Maitum in the province of Sarangani, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kiambing
Target entity description: Kiambing is a barangay (village-level administrative division) of the municipality of Maitum in the province of Sarangani, Philippines.
  • A. Kabuna
    Kabuna is a small village located on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
  • B. Komo
    The Komo are an ethnic group indigenous to western Ethiopia, particularly associated with the Gambela Region, with their own distinct language and cultural traditions.
  • C. Dongo
    Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
  • D. Nasua
    Nasua is a genus of medium-sized, long-snouted mammals commonly known as coatis, native to the Americas and related to raccoons.
  • E. Kiamba
    Kiamba is a coastal municipality in the province of South Cotabato in the Philippines, known for its fishing industry and scenic natural attractions.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbd489c819098233a111442762e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac939bc819081629b9eef20c4e7 completed May 2, 2026, 4:48 p.m.
NEDg Description generation batch_69f62c7b28588190839c35c19856d16f completed May 2, 2026, 4:55 p.m.
NED2 Entity disambiguation (via description) batch_69f62e403a308190a2bba3fefc420932 completed May 2, 2026, 5:02 p.m.
Created at: April 8, 2026, 9:54 p.m.