Triple

T16396922
Position Surface form Disambiguated ID Type / Status
Subject San Narciso, Zambales E398206 entity
Predicate hasBarangay P29835 FINISHED
Object San Jose
San Jose is a barangay (village-level administrative division) within the municipality of San Narciso in the province of Zambales, Philippines.
 E1234382 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 Jose | Statement: [San Narciso, Zambales, hasBarangay, San Jose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Jose
Context triple: [San Narciso, Zambales, hasBarangay, San Jose]
  • A. San Jose
    San Jose is a municipality in the province of Tarlac in the Central Luzon region of the Philippines, known for its predominantly agricultural economy.
  • B. San Jose
    San Jose is a municipality in the province of Batangas in the Philippines, known for its agricultural economy and rural communities.
  • C. San Jose
    San Jose is a coastal municipality in the Philippine province of Romblon known for its island landscapes and fishing communities.
  • D. San Jose
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • E. San Jose
    San Jose is the main town on the island of Tinian in the Northern Mariana Islands, serving as its administrative and population center.
  • 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 Jose
Triple: [San Narciso, Zambales, hasBarangay, San Jose]
Generated description
San Jose is a barangay (village-level administrative division) within the municipality of San Narciso in the province of Zambales, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: San Jose
Target entity description: San Jose is a barangay (village-level administrative division) within the municipality of San Narciso in the province of Zambales, Philippines.
  • A. San Jose
    San Jose is a barangay (village-level administrative division) of the municipality of Ternate in the province of Cavite, Philippines.
  • B. San Jose
    San Jose is a barangay (village-level administrative division) within the municipality of Dumalag in the Philippines.
  • C. San Jose
    San Jose is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • D. San Jose
    San Jose is a municipality in the province of Batangas in the Philippines, known for its agricultural economy and rural communities.
  • E. San Jose
    San Jose is a municipality in the province of Tarlac in the Central Luzon region of the Philippines, known for its predominantly agricultural economy.
  • 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_6a00b276be5c8190a42ce541168ab7d0 completed May 10, 2026, 4:29 p.m.
NEDg Description generation batch_6a00b33f21a48190b3178aa1241bb85a completed May 10, 2026, 4:33 p.m.
NED2 Entity disambiguation (via description) batch_6a00b3afb3708190ab7d78561a2e778c completed May 10, 2026, 4:34 p.m.
Created at: April 10, 2026, 5:09 a.m.