Triple

T8079386
Position Surface form Disambiguated ID Type / Status
Subject Aurora E188575 entity
Predicate hasMunicipality P847 FINISHED
Object Dinalungan
Dinalungan is a coastal municipality in the province of Aurora in the Philippines, known for its rural landscapes and Pacific shoreline.
E715070 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: Dinalungan | Statement: [Aurora, hasMunicipality, Dinalungan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dinalungan
Context triple: [Aurora, hasMunicipality, Dinalungan]
  • A. Dapitan
    Dapitan is a historic coastal city in the Zamboanga Peninsula of the Philippines, best known as the place of exile of national hero José Rizal.
  • B. Dumalag
    Dumalag is a municipality in the province of Capiz in the Western Visayas region of the Philippines, known for its rural landscapes and small-town character.
  • C. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • D. Lalakay
    Lalakay is a barangay (village-level administrative division) within the municipality of Los Baños in the province of Laguna, Philippines.
  • E. 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.
  • 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: Dinalungan
Triple: [Aurora, hasMunicipality, Dinalungan]
Generated description
Dinalungan is a coastal municipality in the province of Aurora in the Philippines, known for its rural landscapes and Pacific shoreline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dinalungan
Target entity description: Dinalungan is a coastal municipality in the province of Aurora in the Philippines, known for its rural landscapes and Pacific shoreline.
  • A. Dapitan
    Dapitan is a historic coastal city in the Zamboanga Peninsula of the Philippines, best known as the place of exile of national hero José Rizal.
  • B. Dumalag
    Dumalag is a municipality in the province of Capiz in the Western Visayas region of the Philippines, known for its rural landscapes and small-town character.
  • C. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • D. Lalakay
    Lalakay is a barangay (village-level administrative division) within the municipality of Los Baños in the province of Laguna, Philippines.
  • E. 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.
  • 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_69ca82b662e88190b9323daab8c28a21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb40a3f01c819096a2c9d5d5199fe6 completed March 31, 2026, 3:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbe73549081908e8601aab662725f completed April 1, 2026, 6:42 a.m.
NEDg Description generation batch_69ccc24c5684819093a4f58616122675 completed April 1, 2026, 6:59 a.m.
NED2 Entity disambiguation (via description) batch_69ccc38e85bc8190b0f4b2435a385f47 completed April 1, 2026, 7:04 a.m.
Created at: March 30, 2026, 5:28 p.m.