Triple

T11671576
Position Surface form Disambiguated ID Type / Status
Subject San Salvador Department E277393 entity
Predicate contains P35 FINISHED
Object Santo Tomás
Santo Tomás is a municipality in El Salvador known for its rural character and proximity to the capital, San Salvador.
E940177 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: Santo Tomás | Statement: [San Salvador Department, contains, Santo Tomás]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santo Tomás
Context triple: [San Salvador Department, contains, Santo Tomás]
  • A. Santo Tomas
    Santo Tomas is a small inland municipality in the province of Pampanga in the Philippines, known for its agricultural communities and proximity to major Central Luzon urban centers.
  • B. Santo Tomas
    Santo Tomas is a landlocked agricultural municipality in the province of Davao del Norte on the island of Mindanao in the Philippines.
  • C. Santa Rosa de Lima
    Santa Rosa de Lima is a 17th-century Peruvian mystic and member of the Dominican Order venerated as the first canonized saint of the Americas and the patron saint of Peru and Latin America.
  • D. Santo Domingo de Guzmán
    Santo Domingo de Guzmán is the capital and largest city of the Dominican Republic, serving as its political, economic, and cultural center.
  • E. フランシスコ
    フランシスコは、日本の政治家・麻生太郎が受けたカトリックの洗礼で用いられているキリスト教名である。
  • 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: Santo Tomás
Triple: [San Salvador Department, contains, Santo Tomás]
Generated description
Santo Tomás is a municipality in El Salvador known for its rural character and proximity to the capital, San Salvador.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Santo Tomás
Target entity description: Santo Tomás is a municipality in El Salvador known for its rural character and proximity to the capital, San Salvador.
  • A. Santo Tomas
    Santo Tomas is a small inland municipality in the province of Pampanga in the Philippines, known for its agricultural communities and proximity to major Central Luzon urban centers.
  • B. Santo Tomas
    Santo Tomas is a landlocked agricultural municipality in the province of Davao del Norte on the island of Mindanao in the Philippines.
  • C. Santa Rosa de Lima
    Santa Rosa de Lima is a 17th-century Peruvian mystic and member of the Dominican Order venerated as the first canonized saint of the Americas and the patron saint of Peru and Latin America.
  • D. Santo Domingo de Guzmán
    Santo Domingo de Guzmán is the capital and largest city of the Dominican Republic, serving as its political, economic, and cultural center.
  • E. フランシスコ
    フランシスコは、日本の政治家・麻生太郎が受けたカトリックの洗礼で用いられているキリスト教名である。
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a44264c08190ba1a4a5bcdc9367b completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef13d3a8608190a084d8bbcac4f924 completed April 27, 2026, 7:44 a.m.
NEDg Description generation batch_69ef3551b9a88190a9b30bcb2592628b completed April 27, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69ef51c17078819083f05036f290ce09 completed April 27, 2026, 12:08 p.m.
Created at: April 8, 2026, 9:40 p.m.