Triple

T2329556
Position Surface form Disambiguated ID Type / Status
Subject Soccsksargen E48369 entity
Predicate hasComponentCity P37693 FINISHED
Object Kidapawan
Kidapawan is a city in the Philippines that serves as the capital of Cotabato province on the island of Mindanao.
E344343 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: Kidapawan | Statement: [Soccsksargen, hasComponentCity, Kidapawan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kidapawan
Context triple: [Soccsksargen, hasComponentCity, Kidapawan]
  • A. Dinalupihan
    Dinalupihan is a landlocked municipality in the province of Bataan in the Philippines, known for its agricultural economy and strategic location as a gateway between Central Luzon and the Bataan Peninsula.
  • B. Koronadal
    Koronadal is a city in the Philippines that serves as the capital of South Cotabato and the regional administrative center of Soccsksargen.
  • C. Bayugan
    Bayugan is a component city in the Caraga region of Mindanao in the Philippines, known as an agricultural and commercial hub in its area.
  • D. Tacurong
    Tacurong is a component city in the Philippines located in the Soccsksargen region on the island of Mindanao.
  • E. Davao de Oro
    Davao de Oro is a landlocked province in the Davao Region of Mindanao in the Philippines, known for its gold deposits, agricultural production, and mountainous landscapes.
  • 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: Kidapawan
Triple: [Soccsksargen, hasComponentCity, Kidapawan]
Generated description
Kidapawan is a city in the Philippines that serves as the capital of Cotabato province on the island of Mindanao.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kidapawan
Target entity description: Kidapawan is a city in the Philippines that serves as the capital of Cotabato province on the island of Mindanao.
  • A. Dinalupihan
    Dinalupihan is a landlocked municipality in the province of Bataan in the Philippines, known for its agricultural economy and strategic location as a gateway between Central Luzon and the Bataan Peninsula.
  • B. Koronadal
    Koronadal is a city in the Philippines that serves as the capital of South Cotabato and the regional administrative center of Soccsksargen.
  • C. Bayugan
    Bayugan is a component city in the Caraga region of Mindanao in the Philippines, known as an agricultural and commercial hub in its area.
  • D. Tacurong
    Tacurong is a component city in the Philippines located in the Soccsksargen region on the island of Mindanao.
  • E. Davao de Oro
    Davao de Oro is a landlocked province in the Davao Region of Mindanao in the Philippines, known for its gold deposits, agricultural production, and mountainous landscapes.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc667235c819086140af9db961203 completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2e803e994819085dae09224fae2a3 completed March 12, 2026, 4:21 p.m.
NEDg Description generation batch_69b2e9b82a288190a6c1700e19966de6 completed March 12, 2026, 4:28 p.m.
NED2 Entity disambiguation (via description) batch_69b2ea0d98ec8190beb74a32f46554bc completed March 12, 2026, 4:30 p.m.
Created at: March 4, 2026, 7:50 p.m.