Triple

T2686491
Position Surface form Disambiguated ID Type / Status
Subject South Cotabato E57495 entity
Predicate hasMunicipality P847 FINISHED
Object Kiamba
Kiamba is a coastal municipality in the province of South Cotabato in the Philippines, known for its fishing industry and scenic natural attractions.
E288641 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: Kiamba | Statement: [South Cotabato, hasMunicipality, Kiamba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiamba
Context triple: [South Cotabato, hasMunicipality, Kiamba]
  • A. Kiyombe
    Kiyombe is a regional variety of the Kikongo language spoken by communities in parts of Central Africa.
  • B. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • C. Chambo
    Chambo is a small town in central Ecuador known for its agricultural activities and proximity to the Andean highlands.
  • D. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • E. Kiamu
    Kiamu is a dialect of the Swahili language traditionally spoken in the Lamu (Amu) region of Kenya.
  • 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: Kiamba
Triple: [South Cotabato, hasMunicipality, Kiamba]
Generated description
Kiamba is a coastal municipality in the province of South Cotabato in the Philippines, known for its fishing industry and scenic natural attractions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kiamba
Target entity description: Kiamba is a coastal municipality in the province of South Cotabato in the Philippines, known for its fishing industry and scenic natural attractions.
  • A. Kiyombe
    Kiyombe is a regional variety of the Kikongo language spoken by communities in parts of Central Africa.
  • B. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • C. Chambo
    Chambo is a small town in central Ecuador known for its agricultural activities and proximity to the Andean highlands.
  • D. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • E. Kiamu
    Kiamu is a dialect of the Swahili language traditionally spoken in the Lamu (Amu) region of Kenya.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9ef2fe0819082bbe746ca682a7e completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa07228088190bb4942b3a25c938b completed March 10, 2026, 4:39 a.m.
NEDg Description generation batch_69afa0ff9c10819096d06ead6dc87d04 completed March 10, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_69afa1e4ffb08190a6d96665ee566ea7 completed March 10, 2026, 4:45 a.m.
Created at: March 6, 2026, 9:54 p.m.