Triple

T10944280
Position Surface form Disambiguated ID Type / Status
Subject Davao del Sur E258553 entity
Predicate hasMunicipality P847 FINISHED
Object Kiblawan
Kiblawan is a rural municipality in the province of Davao del Sur in the Philippines, known for its agricultural economy and upland communities.
E896575 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: Kiblawan | Statement: [Davao del Sur, hasMunicipality, Kiblawan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiblawan
Context triple: [Davao del Sur, hasMunicipality, Kiblawan]
  • A. Kawul
    Kawul is an alternative transliteration of the name "Kaul," a surname and community name commonly associated with Kashmiri Pandits from the Kashmir region of the Indian subcontinent.
  • B. Koga
    Koga is a coastal city in Japan known as a residential suburb of Fukuoka with convenient access to the greater Fukuoka metropolitan area.
  • C. Kashira
    Kashira is a historic town in Russia, located south of Moscow on the Oka River and known as a regional industrial and transport center.
  • D. Koubia
    Koubia is a town in the Middle Guinea region of Guinea that serves as an important local administrative and commercial center.
  • E. Kisukuma
    Kisukuma is a Bantu language spoken primarily by the Sukuma people in northern Tanzania.
  • 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: Kiblawan
Triple: [Davao del Sur, hasMunicipality, Kiblawan]
Generated description
Kiblawan is a rural municipality in the province of Davao del Sur in the Philippines, known for its agricultural economy and upland communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kiblawan
Target entity description: Kiblawan is a rural municipality in the province of Davao del Sur in the Philippines, known for its agricultural economy and upland communities.
  • A. Kawul
    Kawul is an alternative transliteration of the name "Kaul," a surname and community name commonly associated with Kashmiri Pandits from the Kashmir region of the Indian subcontinent.
  • B. Koga
    Koga is a coastal city in Japan known as a residential suburb of Fukuoka with convenient access to the greater Fukuoka metropolitan area.
  • C. Kashira
    Kashira is a historic town in Russia, located south of Moscow on the Oka River and known as a regional industrial and transport center.
  • D. Koubia
    Koubia is a town in the Middle Guinea region of Guinea that serves as an important local administrative and commercial center.
  • E. Kisukuma
    Kisukuma is a Bantu language spoken primarily by the Sukuma people in northern Tanzania.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c4d59481908a5900fc8cf9ecc3 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d722972c8190b14637dc9e52ce11 completed April 18, 2026, 12:58 a.m.
NEDg Description generation batch_69e2ff1ddd2c8190b31f5007f7492a4e completed April 18, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_69e3260494bc81909e3dd4829697fb72 completed April 18, 2026, 6:34 a.m.
Created at: April 8, 2026, 9:23 p.m.