Triple

T15421070
Position Surface form Disambiguated ID Type / Status
Subject Monroe Regional Airport E369377 entity
Predicate operator P179 FINISHED
Object City of Monroe E255595 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: City of Monroe | Statement: [Monroe Regional Airport, operator, City of Monroe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Monroe
Context triple: [Monroe Regional Airport, operator, City of Monroe]
  • A. City of Monroe chosen
    The City of Monroe is a municipal government in northeastern Louisiana that serves as the administrative and cultural center of the Monroe metropolitan area.
  • B. Monroe, Louisiana
    Monroe, Louisiana is a city in northeastern Louisiana that serves as a regional hub for commerce, education, and culture along the Ouachita River.
  • C. Old Town Monrovia
    Old Town Monrovia is the historic downtown district of Monrovia, California, known for its preserved early-20th-century architecture, local shops, and community events.
  • D. City of Jackson
    The City of Jackson is the capital and largest city of Mississippi, serving as the state's political, economic, and cultural center.
  • E. City of Jefferson
    City of Jefferson is the municipal government of Jefferson City, Missouri, responsible for providing local public services and managing city-owned facilities and infrastructure.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ebe7b1081908e6b9e6e128a8d5d completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a7adb848190836fb972bc8744f1 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:20 a.m.