Triple

T13737703
Position Surface form Disambiguated ID Type / Status
Subject Cung Le E329993 entity
Predicate residence P75 FINISHED
Object San Jose, California E1776 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 Jose, California | Statement: [Cung Le, residence, San Jose, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Jose, California
Context triple: [Cung Le, residence, San Jose, California]
  • A. San Jose chosen
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • B. San Jose
    San Jose is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • C. San Jose
    San Jose is the main town on the island of Tinian in the Northern Mariana Islands, serving as its administrative and population center.
  • D. San Jose
    San Jose is a coastal municipality in the Philippine province of Negros Oriental known for its rural communities and proximity to Dumaguete City.
  • E. San Jose
    San Jose is a municipality in the province of Tarlac in the Central Luzon region of the Philippines, known for its predominantly agricultural economy.
  • 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_69d80772315881908f980cae40d91664 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69de0204d50c8190a5413cc9a1b26e14 completed April 14, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcd08698e0819084f3098d471e7dc9 completed May 7, 2026, 5:48 p.m.
Created at: April 9, 2026, 9:55 p.m.