Triple

T8079233
Position Surface form Disambiguated ID Type / Status
Subject Batangas E188572 entity
Predicate hasMunicipality P847 FINISHED
Object San Pascual
San Pascual is a coastal municipality in the province of Batangas in the Philippines, known for its mix of residential communities and industrial facilities.
E715064 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 Pascual | Statement: [Batangas, hasMunicipality, San Pascual]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Pascual
Context triple: [Batangas, hasMunicipality, San Pascual]
  • A. San Cosme
    San Cosme is a Mexico City Metro station on Line 2 that serves the San Rafael neighborhood near the historic center of the city.
  • B. Alto de las Piedras
    Alto de las Piedras is an archaeological site in Colombia known for its pre-Columbian stone statues and tombs associated with the ancient San Agustín culture.
  • C. Pozo Almonte
    Pozo Almonte is a small town and commune in northern Chile known as an administrative and service center in the arid Tarapacá desert region.
  • D. San Juan de Flores
    San Juan de Flores is a municipality in central Honduras known for its rural character and location within the Francisco Morazán Department.
  • E. Guayaramerín
    Guayaramerín is a Bolivian town and river port in the Beni Department, located on the Mamoré River near the border with Brazil.
  • 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 Pascual
Triple: [Batangas, hasMunicipality, San Pascual]
Generated description
San Pascual is a coastal municipality in the province of Batangas in the Philippines, known for its mix of residential communities and industrial facilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: San Pascual
Target entity description: San Pascual is a coastal municipality in the province of Batangas in the Philippines, known for its mix of residential communities and industrial facilities.
  • A. San Cosme
    San Cosme is a Mexico City Metro station on Line 2 that serves the San Rafael neighborhood near the historic center of the city.
  • B. Alto de las Piedras
    Alto de las Piedras is an archaeological site in Colombia known for its pre-Columbian stone statues and tombs associated with the ancient San Agustín culture.
  • C. Pozo Almonte
    Pozo Almonte is a small town and commune in northern Chile known as an administrative and service center in the arid Tarapacá desert region.
  • D. San Juan de Flores
    San Juan de Flores is a municipality in central Honduras known for its rural character and location within the Francisco Morazán Department.
  • E. Guayaramerín
    Guayaramerín is a Bolivian town and river port in the Beni Department, located on the Mamoré River near the border with Brazil.
  • 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_69ca82b50c708190863f661d438e68df 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.