Triple

T207855
Position Surface form Disambiguated ID Type / Status
Subject Saint Anne E4646 entity
Predicate languageVariant P5595 FINISHED
Object Santa Ana (Spanish)
Santa Ana is the Spanish-language form of the name Saint Anne, the mother of the Virgin Mary in Christian tradition.
 E26595 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: Santa Ana (Spanish) | Statement: [Saint Anne, languageVariant, Santa Ana (Spanish)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Santa Ana (Spanish)
Context triple: [Saint Anne, languageVariant, Santa Ana (Spanish)]
  • A. San Antonio de los Baños
    San Antonio de los Baños is a Cuban town known for its film school and cultural traditions, located southwest of Havana.
  • B. San Carlos
    San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
  • C. San Borja
    San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
  • D. Navarro
    Navarro is a Spanish surname borne by numerous notable individuals across fields such as film, sports, politics, and academia.
  • E. San Isidro
    San Isidro is an upscale, modern district of Lima, Peru, known for its financial center, embassies, parks, and high-end residential areas.
  • 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: Santa Ana (Spanish)
Triple: [Saint Anne, languageVariant, Santa Ana (Spanish)]
Generated description
Santa Ana is the Spanish-language form of the name Saint Anne, the mother of the Virgin Mary in Christian tradition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Santa Ana (Spanish)
Target entity description: Santa Ana is the Spanish-language form of the name Saint Anne, the mother of the Virgin Mary in Christian tradition.
  • A. San Antonio de los Baños
    San Antonio de los Baños is a Cuban town known for its film school and cultural traditions, located southwest of Havana.
  • B. San Carlos
    San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
  • C. San Borja
    San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
  • D. Navarro
    Navarro is a Spanish surname borne by numerous notable individuals across fields such as film, sports, politics, and academia.
  • E. San Isidro
    San Isidro is an upscale, modern district of Lima, Peru, known for its financial center, embassies, parks, and high-end residential areas.
  • 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_69a25737567c81908f9c505300239181 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c071fac81908f706d1384281182 completed Feb. 28, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69a32f29799c8190a445a231006bf436 completed Feb. 28, 2026, 6:08 p.m.
NEDg Description generation batch_69a32f866fd4819097e93255723602cc completed Feb. 28, 2026, 6:10 p.m.
NED2 Entity disambiguation (via description) batch_69a32fe4faf88190a3637cbfc768522e completed Feb. 28, 2026, 6:11 p.m.
Created at: Feb. 28, 2026, 2:51 a.m.