Triple

T6717433
Position Surface form Disambiguated ID Type / Status
Subject Mateo E153306 entity
Predicate isCognateWith P2527 FINISHED
Object Matias
Matias is a masculine given name of Hebrew origin, related to names like Mateo and Matthew, commonly used in Spanish- and Portuguese-speaking countries.
 E614469 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: Matias | Statement: [Mateo, isCognateWith, Matias]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Matias
Context triple: [Mateo, isCognateWith, Matias]
  • A. Jacobo
    Jacobo is a given name, commonly used in Spanish-speaking cultures, that is related to or derived from the name Jaime.
  • B. Sebastián
    Sebastián is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • C. Andrés
    Andrés is a Spanish given name commonly used as the equivalent of Andrew.
  • D. Jorge
    Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
  • E. Jorge
    Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
  • 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: Matias
Triple: [Mateo, isCognateWith, Matias]
Generated description
Matias is a masculine given name of Hebrew origin, related to names like Mateo and Matthew, commonly used in Spanish- and Portuguese-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Matias
Target entity description: Matias is a masculine given name of Hebrew origin, related to names like Mateo and Matthew, commonly used in Spanish- and Portuguese-speaking countries.
  • A. Jacobo
    Jacobo is a given name, commonly used in Spanish-speaking cultures, that is related to or derived from the name Jaime.
  • B. Sebastián
    Sebastián is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • C. Andrés
    Andrés is a Spanish given name commonly used as the equivalent of Andrew.
  • D. Jorge
    Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
  • E. Jorge
    Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d12765a48190b485176dc2ffa0fa completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7009b9b64819095ae1a65cd72c374 completed March 27, 2026, 10:11 p.m.
NEDg Description generation batch_69c705220cb0819081a70175c150d138 completed March 27, 2026, 10:30 p.m.
NED2 Entity disambiguation (via description) batch_69c705db3098819083ce9a93e429b758 completed March 27, 2026, 10:34 p.m.
Created at: March 27, 2026, 2:07 p.m.