Triple

T2073781
Position Surface form Disambiguated ID Type / Status
Subject Runway 12L/30R E44874 entity
Predicate servesCity P82 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: [Runway 12L/30R, servesCity, San Jose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Jose
Context triple: [Runway 12L/30R, servesCity, 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 chosen
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • C. San Mateo
    San Mateo is a city in California’s San Francisco Bay Area, known for its suburban neighborhoods, parks, and role as a commercial and residential hub on the Peninsula.
  • D. San José
    San José is the capital and largest city of Costa Rica, known for its political, economic, and cultural significance in Central America.
  • E. San José
    San José is a small municipality and town located in the Caldas Department of Colombia, known for its coffee-growing rural landscape in the Andean region.
  • 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_69a88916c2b48190a5ca2e9b12cad3ed completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba101c008190840763d2f28fa8d7 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4c34fb7d881908d45f96f621d26ad completed March 14, 2026, 2:09 a.m.
Created at: March 4, 2026, 7:41 p.m.