Triple

T16396979
Position Surface form Disambiguated ID Type / Status
Subject San Felipe, Zambales E398207 entity
Predicate hasBarangay P29835 FINISHED
Object San Miguel
San Miguel is a barangay (village-level administrative division) within the municipality of San Felipe in the province of Zambales, Philippines.
E1211607 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 Miguel | Statement: [San Felipe, Zambales, hasBarangay, San Miguel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Miguel
Context triple: [San Felipe, Zambales, hasBarangay, San Miguel]
  • A. San Miguel
    San Miguel is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and rural communities.
  • B. San Miguel
    San Miguel is a municipality located in Colombia’s southern Putumayo Department, near the border with Ecuador.
  • C. San Miguel
    San Miguel is a city in the Greater Buenos Aires metropolitan area of Argentina, located in the northwest of Buenos Aires Province.
  • D. San Miguel
    San Miguel is an active stratovolcano in eastern El Salvador, known for its frequent eruptions and prominent conical shape within the Central American volcanic chain.
  • E. San Miguel
    San Miguel is one of the defensive bastions of Fort San Pedro, a historic Spanish colonial fortification in Cebu, Philippines.
  • 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 Miguel
Triple: [San Felipe, Zambales, hasBarangay, San Miguel]
Generated description
San Miguel is a barangay (village-level administrative division) within the municipality of San Felipe in the province of Zambales, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: San Miguel
Target entity description: San Miguel is a barangay (village-level administrative division) within the municipality of San Felipe in the province of Zambales, Philippines.
  • A. San Miguel
    San Miguel is a barangay (village-level administrative division) of the municipality of Botolan in the province of Zambales, Philippines.
  • B. San Miguel
    San Miguel is a barangay (local administrative district) within the highly urbanized city of Taguig in Metro Manila, Philippines.
  • C. San Miguel
    San Miguel is a rural municipality located on the island province of Catanduanes in the Bicol Region of the Philippines.
  • D. San Miguel
    San Miguel is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and rural communities.
  • E. San Miguel
    San Miguel is a rural municipality in the province of Surigao del Sur in the Caraga region of Mindanao, Philippines.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e327cb3c708190b64341cb1410ed81 completed April 18, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c5bcc7c81909dc1d3a9a1b7f50a completed May 10, 2026, 8:05 a.m.
NEDg Description generation batch_6a003dd7e9d481908822da391112eb39 completed May 10, 2026, 8:12 a.m.
NED2 Entity disambiguation (via description) batch_6a003eb6aa748190b0c8866af405794a completed May 10, 2026, 8:15 a.m.
Created at: April 10, 2026, 5:09 a.m.