Triple

T21013652
Position Surface form Disambiguated ID Type / Status
Subject SoFA District E517614 entity
Predicate locatedIn P40 FINISHED
Object San Jose
San Jose is a major city in California’s Silicon Valley known for its tech industry, diverse population, and role as an economic and cultural hub of the region.
E1776 NE FINISHED

How this triple was built (4 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: [SoFA District, locatedIn, San Jose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Jose
Context triple: [SoFA District, locatedIn, San Jose]
  • A. 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.
  • B. 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.
  • C. San Jose
    San Jose is a municipality in the province of Batangas in the Philippines, known for its agricultural economy and rural communities.
  • D. San Jose
    San Jose is a barangay (village-level administrative division) within the municipality of Dumalag in the Philippines.
  • E. San Jose
    San Jose is the principal town and administrative center of the Philippine province of Dinagat Islands.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: San Jose
Triple: [SoFA District, locatedIn, San Jose]
Generated description
San Jose is a major city in California’s Silicon Valley known for its tech industry, diverse population, and role as an economic and cultural hub of the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: San Jose
Target entity description: San Jose is a major city in California’s Silicon Valley known for its tech industry, diverse population, and role as an economic and cultural hub of the region.
  • 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 Occidental Mindoro in the Philippines, known as a commercial and transportation hub for the region.
  • C. 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.
  • D. San Jose
    San Jose is a coastal municipality in the Philippine province of Romblon known for its island landscapes and fishing communities.
  • 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.

Provenance (5 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_69e0b50192308190a284fcc89dd23a49 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc41d57881908b9ab17d1844a8d0 completed April 21, 2026, 4:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a093b40b32c819093685be0ca2ea84a completed May 17, 2026, 3:51 a.m.
NEDg Description generation batch_6a093e2d718c81908cf1b9dc5f2a34d3 completed May 17, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_6a093eccb0b08190a6c8383c607a49d4 completed May 17, 2026, 4:06 a.m.
Created at: April 16, 2026, 1:54 p.m.