Triple

T3550131
Position Surface form Disambiguated ID Type / Status
Subject America Ferrera E75090 entity
Predicate familyName P18 FINISHED
Object Ferrera
Ferrera is a Spanish-origin surname most prominently associated with American actress and producer America Ferrera.
 E368033 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: Ferrera | Statement: [America Ferrera, familyName, Ferrera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ferrera
Context triple: [America Ferrera, familyName, Ferrera]
  • A. Blasco
    Blasco is a masculine given name of Spanish origin, historically borne by notable figures such as colonial administrators and writers.
  • B. Gaspar
    Gaspar is the given name of Gaspar de Guzmán, Count-Duke of Olivares, a powerful 17th-century Spanish royal favorite and statesman under King Philip IV.
  • C. Federico
    Federico is the Italian and Spanish form of the given name Frederick, commonly used in Romance-language countries.
  • D. Amadeo
    Amadeo is a small agricultural municipality in the province of Cavite in the Philippines, known particularly for its coffee production.
  • E. Baltasar
    Baltasar is a variant of the name Belshazzar, historically associated with the last king of Babylon mentioned in the biblical Book of Daniel.
  • 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: Ferrera
Triple: [America Ferrera, familyName, Ferrera]
Generated description
Ferrera is a Spanish-origin surname most prominently associated with American actress and producer America Ferrera.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ferrera
Target entity description: Ferrera is a Spanish-origin surname most prominently associated with American actress and producer America Ferrera.
  • A. Blasco
    Blasco is a masculine given name of Spanish origin, historically borne by notable figures such as colonial administrators and writers.
  • B. Gaspar
    Gaspar is the given name of Gaspar de Guzmán, Count-Duke of Olivares, a powerful 17th-century Spanish royal favorite and statesman under King Philip IV.
  • C. Federico
    Federico is the Italian and Spanish form of the given name Frederick, commonly used in Romance-language countries.
  • D. Amadeo
    Amadeo is a small agricultural municipality in the province of Cavite in the Philippines, known particularly for its coffee production.
  • E. Baltasar
    Baltasar is a variant of the name Belshazzar, historically associated with the last king of Babylon mentioned in the biblical Book of Daniel.
  • 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_69ad85d33c6c819081d5ac1df13b5680 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbfd38c8c8190a4591689ad57c998 completed March 8, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38be9335c81909ba546a079134c8f completed March 13, 2026, 4 a.m.
NEDg Description generation batch_69b38c5cfb608190b451be14246d5481 completed March 13, 2026, 4:02 a.m.
NED2 Entity disambiguation (via description) batch_69b38ce0e1688190a7ee3d079fb83f3d completed March 13, 2026, 4:04 a.m.
Created at: March 8, 2026, 3:20 p.m.