Triple

T22934796
Position Surface form Disambiguated ID Type / Status
Subject Banaue E569551 entity
Predicate hasBarangay P29835 FINISHED
Object San Fernando
San Fernando is a barangay (village-level administrative division) within the municipality of Banaue in Ifugao, Philippines.
E1562414 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: San Fernando | Statement: [Banaue, hasBarangay, San Fernando]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Fernando
Context triple: [Banaue, hasBarangay, San Fernando]
  • A. San Fernando
    San Fernando is a major industrial and commercial city located in the southern part of Trinidad, known for its energy sector and bustling urban center.
  • B. San Fernando
    San Fernando is a principal urban center and agricultural hub in central Chile’s O’Higgins Region.
  • C. San Fernando
    San Fernando is a locality within the municipality of Huixquilucan in the State of Mexico, forming part of the greater Mexico City metropolitan area.
  • D. San Fernando
    San Fernando is a small independent city in Los Angeles County, California, surrounded by but administratively separate from the San Fernando Valley region of Los Angeles.
  • E. San Fernando
    San Fernando is a municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous surroundings.
  • 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: San Fernando
Triple: [Banaue, hasBarangay, San Fernando]
Generated description
San Fernando is a barangay (village-level administrative division) within the municipality of Banaue in Ifugao, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: San Fernando
Target entity description: San Fernando is a barangay (village-level administrative division) within the municipality of Banaue in Ifugao, Philippines.
  • A. San Fernando
    San Fernando is a coastal municipality located in the island province of Romblon in the Philippines.
  • B. San Fernando
    San Fernando is a coastal municipality in the province of Cebu in the Philippines, situated within the greater Metro Cebu area.
  • C. San Fernando
    San Fernando is a coastal municipality in the Philippine province of Masbate, known for its rural communities and fishing-based local economy.
  • D. San Fernando
    San Fernando is a Philippine city on the island of Luzon known as a regional commercial and administrative center.
  • E. San Fernando
    San Fernando is a municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous surroundings.
  • 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_69e24590862c8190858f180ad302adab completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18134484c8190b7311606c17d058d completed April 29, 2026, 3:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bc24ea8bc8190bb7cb6e9475d6641 completed May 19, 2026, 1:52 a.m.
NEDg Description generation batch_6a0bc3dea31c8190ab517e43c9061eec completed May 19, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_6a0bc46fd3d0819094a532a8d6a0b9b2 completed May 19, 2026, 2:01 a.m.
Created at: April 17, 2026, 3:44 p.m.