Triple

T16487111
Position Surface form Disambiguated ID Type / Status
Subject Doris Salcedo E400474 entity
Predicate familyName P18 FINISHED
Object Salcedo
Salcedo is a Spanish-origin surname borne by various notable individuals, including artists, politicians, and athletes across the Spanish-speaking world.
 E1216173 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: Salcedo | Statement: [Doris Salcedo, familyName, Salcedo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Salcedo
Context triple: [Doris Salcedo, familyName, Salcedo]
  • A. Salcedo
    Salcedo is a coastal municipality in the province of Eastern Samar in the Philippines, known for its fishing communities and rural landscapes.
  • B. Salcedo
    Salcedo is a town in Ecuador’s Cotopaxi Province known as a gateway to the remote Llanganates National Park and for its traditional Andean culture.
  • C. Salcedo
    Salcedo is a rural municipality in the province of Ilocos Sur in the Philippines, known for its agricultural communities and mountainous landscapes.
  • D. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • E. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • 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: Salcedo
Triple: [Doris Salcedo, familyName, Salcedo]
Generated description
Salcedo is a Spanish-origin surname borne by various notable individuals, including artists, politicians, and athletes across the Spanish-speaking world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Salcedo
Target entity description: Salcedo is a Spanish-origin surname borne by various notable individuals, including artists, politicians, and athletes across the Spanish-speaking world.
  • A. Salcedo
    Salcedo is a coastal municipality in the province of Eastern Samar in the Philippines, known for its fishing communities and rural landscapes.
  • B. Salcedo
    Salcedo is a rural municipality in the province of Ilocos Sur in the Philippines, known for its agricultural communities and mountainous landscapes.
  • C. Salcedo
    Salcedo is a town in Ecuador’s Cotopaxi Province known as a gateway to the remote Llanganates National Park and for its traditional Andean culture.
  • D. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • E. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e078d0c8190a5698a5eb9df22d4 completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00582275308190a0fb3944d74916cf completed May 10, 2026, 10:04 a.m.
NEDg Description generation batch_6a0058a1c51c81908f49db448a4d0365 completed May 10, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_6a00595837c4819093f1a1a35185bc4b completed May 10, 2026, 10:09 a.m.
Created at: April 10, 2026, 5:13 a.m.