Triple

T16793690
Position Surface form Disambiguated ID Type / Status
Subject Río Piedras E408176 entity
Predicate partOf P40 FINISHED
Object San Juan E663 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: [Río Piedras, partOf, San Juan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Juan
Context triple: [Río Piedras, partOf, San Juan]
  • A. San Juan chosen
    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.
  • B. San Juan
    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.
  • C. San Juan
    San Juan is a coastal municipality on Siquijor Island in the Philippines known for its beaches, dive spots, and laid-back tourist resorts.
  • D. San Juan
    San Juan is a neighborhood within the municipality of Telde on the island of Gran Canaria in Spain’s Canary Islands.
  • E. San Juan
    San Juan is a coastal municipality in the Philippine province of Batangas known for its beaches, dive spots, and heritage sites.
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2a8b66c8190b83d8af85d2b23a8 completed April 18, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb0adc408190a9cbfefdef8c669e completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:22 a.m.