Triple

T19939113
Position Surface form Disambiguated ID Type / Status
Subject Runway 08R/26L E479255 entity
Predicate cityServed P82 FINISHED
Object El Paso NE NERFINISHED

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: El Paso | Statement: [Runway 08R/26L, cityServed, El Paso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: El Paso
Context triple: [Runway 08R/26L, cityServed, El Paso]
  • A. El Paso chosen
    El Paso is a large border city in far western Texas known for its strong cultural ties with Mexico and its role as a major economic and transportation hub in the region.
  • B. El Paso
    El Paso is a municipality on the Spanish island of La Palma in the Canary Islands, known for its volcanic landscapes and proximity to the Cumbre Vieja ridge.
  • C. Laredo
    Laredo is a coastal town in northern Spain’s Cantabria region, known for its long sandy beaches and historic old quarter.
  • D. Laredo
    Laredo is a base-level trim of the Jeep Grand Cherokee SUV, offering essential features at a more affordable price point.
  • E. Nogales
    Nogales is a municipality and town in the state of Veracruz, Mexico, known for its mountainous terrain and role as part of the Orizaba metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e522a17c819095165d4d24939fd8 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a19d77c819088bce99c94568d0d completed April 20, 2026, 4:53 p.m.
Created at: April 10, 2026, 1:53 p.m.