Triple

T8864383
Position Surface form Disambiguated ID Type / Status
Subject San Leandro E210976 entity
Predicate neighboringCity P988 FINISHED
Object San Lorenzo E481737 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 Lorenzo | Statement: [San Leandro, neighboringCity, San Lorenzo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Lorenzo
Context triple: [San Leandro, neighboringCity, San Lorenzo]
  • A. San Lorenzo
    San Lorenzo is a historic church in the Italian town of Spello, known for its medieval architecture and religious significance.
  • B. San Lorenzo
    San Lorenzo is a municipality in the central-eastern region of Puerto Rico known for its rural landscapes and small-town character.
  • C. San Lorenzo
    San Lorenzo is a coastal municipality on the island province of Guimaras in the Philippines, known for its rural communities and agricultural landscape.
  • D. San Lorenzo
    San Lorenzo is an upscale commercial and residential district in Makati, Metro Manila, known for its gated villages, shopping centers, and proximity to the central business area.
  • E. San Lorenzo chosen
    San Lorenzo is an unincorporated community in Alameda County, California, located in the East Bay region of the San Francisco Bay Area.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610569d08190b108107dfe397f18 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0caccd88190b6464f53d0239e47 completed April 3, 2026, 11:13 a.m.
Created at: March 30, 2026, 6:51 p.m.