Triple

T2632079
Position Surface form Disambiguated ID Type / Status
Subject Mandaluyong E59656 entity
Predicate borderedBy P224 FINISHED
Object San Juan E274337 NE FINISHED

How this triple was built (2 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 Juan | Statement: [Mandaluyong, borderedBy, San Juan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Juan
Context triple: [Mandaluyong, borderedBy, San Juan]
  • A. San Juan
    San Juan is an Argentine wine-producing region recognized for its significant Malbec production.
  • B. San Juan
    San Juan is a suburban town in Trinidad and Tobago located just east of the capital, Port of Spain, known for its bustling commercial activity and residential communities.
  • C. San Juan chosen
    San Juan is a highly urbanized city in Metro Manila, Philippines, known for its historical sites, dense residential and commercial areas, and role in the capital region’s urban core.
  • D. San Juan
    San Juan is the largest city and main cultural, economic, and tourism hub of Puerto Rico, known for its historic colonial architecture and vibrant coastal setting.
  • E. Loíza
    Loíza is a coastal municipality in Puerto Rico known for its rich Afro-Puerto Rican culture, traditional Bomba music and dance, and vibrant religious and folk festivals.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c6e540819087c7f92432b27b0f completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce7a1c908190919280545ae4443c completed March 10, 2026, 7:55 a.m.
Created at: March 6, 2026, 9:50 p.m.