Triple

T785025
Position Surface form Disambiguated ID Type / Status
Subject Interstate 35E (Texas) E16581 entity
Predicate hasCommuterTraffic P19600 FINISHED
Object heavy 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: heavy | Statement: [Interstate 35E (Texas), hasCommuterTraffic, heavy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCommuterTraffic
Context triple: [Interstate 35E (Texas), hasCommuterTraffic, heavy]
  • A. hasCommuterOrientation
    Indicates that an entity is designed or intended primarily for use by commuters, emphasizing suitability for regular travel between home and work or study.
  • B. hasCommuterPattern
    Indicates that there is a characteristic or recurring pattern in how an entity regularly travels between locations, typically for work or daily activities.
  • C. hasTrafficDirection
    Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
  • D. isCommuterRegionFor
    Indicates that one region primarily serves as a residential base whose inhabitants regularly travel to another region for work or daily activities.
  • E. transportationImpact
    Indicates how one entity’s transportation-related activities or characteristics affect another entity or the surrounding environment.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a76b0d6c8190a09b1a0bd4a6eeec completed March 1, 2026, 8:54 p.m.
PD Predicate disambiguation batch_69a4a50db97c8190a1c55673f4a357b4 completed March 1, 2026, 8:43 p.m.
PDg Predicate description generation batch_69a4a67e69288190b3dc278c5bd94155 completed March 1, 2026, 8:50 p.m.
Created at: March 1, 2026, 7:37 p.m.