Triple

T254205
Position Surface form Disambiguated ID Type / Status
Subject Southwest Airlines E5400 entity
Predicate routeNetworkCharacteristic P8860 FINISHED
Object point-to-point network LITERAL 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: point-to-point network | Statement: [Southwest Airlines, routeNetworkCharacteristic, point-to-point network]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: routeNetworkCharacteristic
Context triple: [Southwest Airlines, routeNetworkCharacteristic, point-to-point network]
  • A. roadFeature
    Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
  • B. streetNetwork
    Indicates the layout and connectivity relationships among streets within a geographic area, including how roads intersect, link, and form a navigable network.
  • C. isPublicRoadNetwork
    Indicates that a given road network is officially designated for public use and accessible to the general public for transportation.
  • D. routeNumber
    Indicates the specific identifying number assigned to a route within a transportation or delivery network.
  • E. transportCorridor
    Indicates a route or pathway used to move people, goods, or resources between locations.
  • F. None of above. chosen

Provenance (4 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d548cac819081b1636b2a057c62 completed Feb. 28, 2026, 3:13 a.m.
PD Predicate disambiguation batch_69a25b678d6c81909780e1995c1ca691 completed Feb. 28, 2026, 3:05 a.m.
PDg Predicate description generation batch_69a25c2ca46c81908c61696f31e59a98 completed Feb. 28, 2026, 3:08 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.