Triple

T12758406
Position Surface form Disambiguated ID Type / Status
Subject CEFCU Stadium E304920 entity
Predicate city P40 FINISHED
Object San Jose 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 | Statement: [CEFCU Stadium, city, San Jose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Jose
Context triple: [CEFCU Stadium, city, San Jose]
  • 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 Philippine province of Negros Oriental known for its rural communities and proximity to Dumaguete City.
  • C. San Jose
    San Jose is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • D. 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.
  • E. San Jose
    San Jose is a municipality in the province of Batangas in the Philippines, known for its agricultural economy and rural communities.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d8d3eb08190ae998df5cc6d9ba6 completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5b196bc8190a643f2b534497476 completed May 3, 2026, 7:13 a.m.
Created at: April 9, 2026, 5:27 p.m.