Triple

T3686822
Position Surface form Disambiguated ID Type / Status
Subject Sebastián E78243 entity
Predicate shortForm P43 FINISHED
Object Seba
Seba is a common short form or nickname for the given name Sebastián, frequently used in Spanish-speaking countries.
 E380342 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: Seba | Statement: [Sebastián, shortForm, Seba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Seba
Context triple: [Sebastián, shortForm, Seba]
  • A. Orlybus
    Orlybus is a dedicated airport shuttle bus service connecting central Paris with Orly Airport.
  • B. Maurus
    Maurus is a masculine given name of Latin origin, historically associated with early Christian saints and used as a variant of names like Maurice.
  • C. Sucúa
    Sucúa is a small town in the Amazonian region of Ecuador known for its lush rainforest surroundings and indigenous Shuar culture.
  • D. Branta
    Branta is a genus of black geese that includes species such as the barnacle goose, brant goose, and the Hawaiian nēnē.
  • E. Esek
    Esek is a masculine given name most notably borne by Esek Hopkins, the first Commander-in-Chief of the Continental Navy during the American Revolutionary War.
  • 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: Seba
Triple: [Sebastián, shortForm, Seba]
Generated description
Seba is a common short form or nickname for the given name Sebastián, frequently used in Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Seba
Target entity description: Seba is a common short form or nickname for the given name Sebastián, frequently used in Spanish-speaking countries.
  • A. Orlybus
    Orlybus is a dedicated airport shuttle bus service connecting central Paris with Orly Airport.
  • B. Maurus
    Maurus is a masculine given name of Latin origin, historically associated with early Christian saints and used as a variant of names like Maurice.
  • C. Sucúa
    Sucúa is a small town in the Amazonian region of Ecuador known for its lush rainforest surroundings and indigenous Shuar culture.
  • D. Branta
    Branta is a genus of black geese that includes species such as the barnacle goose, brant goose, and the Hawaiian nēnē.
  • E. Esek
    Esek is a masculine given name most notably borne by Esek Hopkins, the first Commander-in-Chief of the Continental Navy during the American Revolutionary War.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4c7e2bc81909356c8b0ed90feed completed March 8, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3c10f6481908feed99cddc56d47 completed March 14, 2026, 2:11 a.m.
NEDg Description generation batch_69b4c7bd861c8190a1a7887f6d7fd6de completed March 14, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_69b4c83085488190a48c6e4786d275e2 completed March 14, 2026, 2:30 a.m.
Created at: March 8, 2026, 3:26 p.m.