Triple

T2047609
Position Surface form Disambiguated ID Type / Status
Subject A7 motorway E45488 entity
Predicate hasSectionWithSpeedLimit P36051 FINISHED
Object urban areas such as Hamburg 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: urban areas such as Hamburg | Statement: [A7 motorway, hasSectionWithSpeedLimit, urban areas such as Hamburg]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSectionWithSpeedLimit
Context triple: [A7 motorway, hasSectionWithSpeedLimit, urban areas such as Hamburg]
  • A. hasSpeedLimit
    Indicates that a specified maximum allowable speed is imposed on the associated entity or context.
  • B. hasSpeedLimitRange
    Indicates that there is a specified minimum and maximum speed limit applicable to a given context or segment.
  • C. hasTrafficControl
    Indicates that some form of traffic management or regulation mechanism is present or applied to a given route, intersection, or transportation element.
  • D. hasExpresswaySection
    Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
  • E. trafficRestriction
    Indicates a limitation or prohibition on the movement or flow of traffic between entities, such as vehicles, routes, or areas.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abbc2c3f6c8190aff07097b2654e52 completed March 7, 2026, 5:48 a.m.
PD Predicate disambiguation batch_69abb7aa00d4819086d347d9a08f81a0 completed March 7, 2026, 5:29 a.m.
PDg Predicate description generation batch_69abbc2b07d48190ba9d67353167b472 completed March 7, 2026, 5:48 a.m.
Created at: March 4, 2026, 7:39 p.m.