Triple

T16979140
Position Surface form Disambiguated ID Type / Status
Subject Santa Ignacia E411894 entity
Predicate hasBarangay P29835 FINISHED
Object Vargas
Vargas is a barangay (village-level administrative division) of the municipality of Santa Ignacia in the province of Tarlac, Philippines.
 E1243528 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: Vargas | Statement: [Santa Ignacia, hasBarangay, Vargas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vargas
Context triple: [Santa Ignacia, hasBarangay, Vargas]
  • A. Vargas
    Vargas is a coastal state in northern Venezuela known for its Caribbean shoreline, proximity to Caracas, and role as a key transport and tourism hub.
  • B. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • C. Burque
    Burque is a colloquial nickname commonly used to refer to the city of Albuquerque, New Mexico.
  • D. Rojas
    Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
  • E. Vázquez
    Vázquez is a Spanish-language surname commonly found in Spain and Latin America, borne by various notable figures in entertainment, sports, and public life.
  • 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: Vargas
Triple: [Santa Ignacia, hasBarangay, Vargas]
Generated description
Vargas is a barangay (village-level administrative division) of the municipality of Santa Ignacia in the province of Tarlac, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vargas
Target entity description: Vargas is a barangay (village-level administrative division) of the municipality of Santa Ignacia in the province of Tarlac, Philippines.
  • A. Vargas
    Vargas is a coastal state in northern Venezuela known for its Caribbean shoreline, proximity to Caracas, and role as a key transport and tourism hub.
  • B. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • C. Burque
    Burque is a colloquial nickname commonly used to refer to the city of Albuquerque, New Mexico.
  • D. Rojas
    Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
  • E. Vázquez
    Vázquez is a Spanish-language surname commonly found in Spain and Latin America, borne by various notable figures in entertainment, sports, and public life.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d185a9408190a991bf8a1ef694f0 completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d477f7ec81909f1f0243004c9050 completed May 10, 2026, 6:54 p.m.
NEDg Description generation batch_6a00d5503be88190ac15a327ff3782ec completed May 10, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_6a00d66e450c8190ae0befd3d7875ed8 completed May 10, 2026, 7:03 p.m.
Created at: April 10, 2026, 5:32 a.m.