Triple

T1354536
Position Surface form Disambiguated ID Type / Status
Subject Nayarit E28956 entity
Predicate hasTouristDestination P6629 FINISHED
Object San Pancho
San Pancho is a laid-back Pacific coastal village in Mexico known for its beaches, surf culture, and vibrant arts and community scene.
E160368 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: San Pancho | Statement: [Nayarit, hasTouristDestination, San Pancho]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Pancho
Context triple: [Nayarit, hasTouristDestination, San Pancho]
  • A. San Pedro
    San Pedro is a coastal neighborhood in the city of Los Angeles known for its busy port, waterfront attractions, and maritime heritage.
  • B. San Pedro
    San Pedro is a Chilean commune and town located within the Santiago Metropolitan Region, known for its rural character and agricultural activities.
  • C. Rosarito
    Rosarito is a coastal resort city in northern Baja California, Mexico, known for its beaches, tourism, and proximity to the U.S. border.
  • D. Puerto Escondido
    Puerto Escondido is a coastal town and popular surfing and beach tourism destination on Mexico’s Pacific coast in the state of Oaxaca.
  • E. Acapulco
    Acapulco is a historic Mexican Pacific coastal city that flourished as a major colonial-era seaport and remains a prominent tourist destination.
  • 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: San Pancho
Triple: [Nayarit, hasTouristDestination, San Pancho]
Generated description
San Pancho is a laid-back Pacific coastal village in Mexico known for its beaches, surf culture, and vibrant arts and community scene.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: San Pancho
Target entity description: San Pancho is a laid-back Pacific coastal village in Mexico known for its beaches, surf culture, and vibrant arts and community scene.
  • A. San Pedro
    San Pedro is a coastal neighborhood in the city of Los Angeles known for its busy port, waterfront attractions, and maritime heritage.
  • B. San Pedro
    San Pedro is a Chilean commune and town located within the Santiago Metropolitan Region, known for its rural character and agricultural activities.
  • C. Rosarito
    Rosarito is a coastal resort city in northern Baja California, Mexico, known for its beaches, tourism, and proximity to the U.S. border.
  • D. Puerto Escondido
    Puerto Escondido is a coastal town and popular surfing and beach tourism destination on Mexico’s Pacific coast in the state of Oaxaca.
  • E. Acapulco
    Acapulco is a historic Mexican Pacific coastal city that flourished as a major colonial-era seaport and remains a prominent tourist destination.
  • 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_69a498571d248190a0ac9eb02d97097f completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c28afc848190925d8b2f9aeac12d completed March 1, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde1555048190b73c1616d1979b08 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acdee073fc819098c906d91870b317 completed March 8, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_69ace0a7ddc08190a44be1707587351b completed March 8, 2026, 2:36 a.m.
Created at: March 1, 2026, 7:56 p.m.