Triple

T11109372
Position Surface form Disambiguated ID Type / Status
Subject Daanbantayan E262714 entity
Predicate hasBarangay P29835 FINISHED
Object Talisay
Talisay is a coastal barangay of the municipality of Daanbantayan in northern Cebu, Philippines.
E930318 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: Talisay | Statement: [Daanbantayan, hasBarangay, Talisay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Talisay
Context triple: [Daanbantayan, hasBarangay, Talisay]
  • A. Talisay
    Talisay is a city in the Philippine province of Negros Occidental known for its sugarcane industry and historical landmarks.
  • B. Talisay
    Talisay is a coastal municipality in the Philippine province of Camarines Norte known for its rural communities and access to fishing and agricultural resources.
  • C. Talisay City
    Talisay City is a coastal component city in the province of Cebu in the Philippines, known for its historical significance and proximity to Metro Cebu.
  • D. Masbate City
    Masbate City is a coastal component city and the capital of Masbate Province in the Philippines, known as a commercial and administrative center in the Bicol Region.
  • E. Calbayog
    Calbayog is a coastal city in the province of Samar in the Philippines, known as a regional hub for trade, culture, and transportation in Eastern Visayas.
  • 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: Talisay
Triple: [Daanbantayan, hasBarangay, Talisay]
Generated description
Talisay is a coastal barangay of the municipality of Daanbantayan in northern Cebu, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Talisay
Target entity description: Talisay is a coastal barangay of the municipality of Daanbantayan in northern Cebu, Philippines.
  • A. Talisay
    Talisay is a city in the Philippine province of Negros Occidental known for its sugarcane industry and historical landmarks.
  • B. Talisay
    Talisay is a coastal municipality in the Philippine province of Camarines Norte known for its rural communities and access to fishing and agricultural resources.
  • C. Talisay City
    Talisay City is a coastal component city in the province of Cebu in the Philippines, known for its historical significance and proximity to Metro Cebu.
  • D. Masbate City
    Masbate City is a coastal component city and the capital of Masbate Province in the Philippines, known as a commercial and administrative center in the Bicol Region.
  • E. Calbayog
    Calbayog is a coastal city in the province of Samar in the Philippines, known as a regional hub for trade, culture, and transportation in Eastern Visayas.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a6896c0819082685b5b4600d158 completed April 9, 2026, 12:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69e623e44c188190b5b83cf8f397554c completed April 20, 2026, 1:02 p.m.
NEDg Description generation batch_69e62aee8fb88190b5973c61e692087f completed April 20, 2026, 1:32 p.m.
NED2 Entity disambiguation (via description) batch_69e67394e7f081908fcc602c84eb4a65 completed April 20, 2026, 6:42 p.m.
Created at: April 8, 2026, 9:27 p.m.