Triple

T11091296
Position Surface form Disambiguated ID Type / Status
Subject Davao Oriental E262260 entity
Predicate contains P35 FINISHED
Object Lupon
Lupon is a coastal municipality in the province of Davao Oriental on the island of Mindanao in the Philippines.
E904216 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: Lupon | Statement: [Davao Oriental, contains, Lupon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lupon
Context triple: [Davao Oriental, contains, Lupon]
  • A. Lupao
    Lupao is a landlocked agricultural municipality in the province of Nueva Ecija in the Central Luzon region of the Philippines.
  • B. Maragondon
    Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
  • C. Borongan
    Borongan is a coastal city in Eastern Samar, Philippines, known as a regional center and gateway to the natural attractions of Samar Island.
  • D. Liboi
    Liboi is a small Kenyan border town in the arid northeast near Somalia, serving as a local trading and transit point.
  • E. Kapyong
    Kapyong is a Korean War battlefield in South Korea renowned for a pivotal 1951 engagement in which outnumbered UN forces, including Canadian troops, halted a major Chinese offensive.
  • 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: Lupon
Triple: [Davao Oriental, contains, Lupon]
Generated description
Lupon is a coastal municipality in the province of Davao Oriental on the island of Mindanao in the Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lupon
Target entity description: Lupon is a coastal municipality in the province of Davao Oriental on the island of Mindanao in the Philippines.
  • A. Lupao
    Lupao is a landlocked agricultural municipality in the province of Nueva Ecija in the Central Luzon region of the Philippines.
  • B. Maragondon
    Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
  • C. Borongan
    Borongan is a coastal city in Eastern Samar, Philippines, known as a regional center and gateway to the natural attractions of Samar Island.
  • D. Liboi
    Liboi is a small Kenyan border town in the arid northeast near Somalia, serving as a local trading and transit point.
  • E. Kapyong
    Kapyong is a Korean War battlefield in South Korea renowned for a pivotal 1951 engagement in which outnumbered UN forces, including Canadian troops, halted a major Chinese offensive.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799ebae8c8190987b474adb7ede47 completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7c586808190a576803b7406a49e completed April 18, 2026, 8:21 p.m.
NEDg Description generation batch_69e3f2cafc008190a3504999297f1e4e completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f488819081908f9a4225279cde6b completed April 18, 2026, 9:15 p.m.
Created at: April 8, 2026, 9:27 p.m.