Triple

T9203112
Position Surface form Disambiguated ID Type / Status
Subject California State Route 99 E220897 entity
Predicate passesThrough P225 FINISHED
Object Delano E110863 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: Delano | Statement: [California State Route 99, passesThrough, Delano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Delano
Context triple: [California State Route 99, passesThrough, Delano]
  • A. Delano
    Delano is the middle name of Franklin D. Roosevelt, the 32nd president of the United States.
  • B. Delano chosen
    Delano is a small agricultural city in California’s Central Valley known for its table grape production and historic role in the farm labor movement.
  • C. Davenport
    Davenport is an English surname of Norman origin that has been borne by various notable figures in mathematics, politics, and the arts.
  • D. Davenport
    Davenport is a historic community in Toronto, Ontario, known for its early settlement along Davenport Road and its role in the city’s industrial and residential development.
  • E. de Kalb
    De Kalb is a German-born French military officer who served as a major general in the Continental Army during the American Revolutionary War and became a symbol of foreign support for the American cause.
  • 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_69ca83e8e9248190862cf3e41693b310 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd944e6208190adfcc7f75197387d completed April 1, 2026, 8:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c4953588190aa842de269eee56c completed April 4, 2026, 12:33 a.m.
Created at: March 30, 2026, 7:26 p.m.