Triple

T2375882
Position Surface form Disambiguated ID Type / Status
Subject Cebu E46197 entity
Predicate hasPart P35 FINISHED
Object Argao
Argao is a coastal municipality in the southeastern part of Cebu, Philippines, known for its Spanish-era heritage structures and traditional delicacies.
E373285 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: Argao | Statement: [Cebu, hasPart, Argao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Argao
Context triple: [Cebu, hasPart, Argao]
  • A. 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.
  • B. Guihulngan
    Guihulngan is a coastal city and commercial hub in the northern part of Negros Oriental in the Philippines.
  • C. Koronadal
    Koronadal is a city in the Philippines that serves as the capital of South Cotabato and the regional administrative center of Soccsksargen.
  • D. Surigao City
    Surigao City is a coastal city in the Caraga region of northeastern Mindanao in the Philippines, known as the “City of Island Adventures” for its numerous islands, beaches, and marine attractions.
  • E. Balamban
    Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
  • 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: Argao
Triple: [Cebu, hasPart, Argao]
Generated description
Argao is a coastal municipality in the southeastern part of Cebu, Philippines, known for its Spanish-era heritage structures and traditional delicacies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Argao
Target entity description: Argao is a coastal municipality in the southeastern part of Cebu, Philippines, known for its Spanish-era heritage structures and traditional delicacies.
  • A. 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.
  • B. Guihulngan
    Guihulngan is a coastal city and commercial hub in the northern part of Negros Oriental in the Philippines.
  • C. Koronadal
    Koronadal is a city in the Philippines that serves as the capital of South Cotabato and the regional administrative center of Soccsksargen.
  • D. Surigao City
    Surigao City is a coastal city in the Caraga region of northeastern Mindanao in the Philippines, known as the “City of Island Adventures” for its numerous islands, beaches, and marine attractions.
  • E. Balamban
    Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
  • 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_69a88a1554a48190a0180682bcf099be completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc794eee481908163148e1e666d9b completed March 7, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69b432e588308190bd331d7b8776e546 completed March 13, 2026, 3:53 p.m.
NEDg Description generation batch_69b436c3d6a0819081478d3cafb6f40b completed March 13, 2026, 4:09 p.m.
NED2 Entity disambiguation (via description) batch_69b43725f4108190b8f19fc730b72d98 completed March 13, 2026, 4:11 p.m.
Created at: March 4, 2026, 7:57 p.m.