Triple

T607433
Position Surface form Disambiguated ID Type / Status
Subject Lombard Street E12024 entity
Predicate hasTrafficControl P17040 FINISHED
Object seasonal measures to manage tourist congestion 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: seasonal measures to manage tourist congestion | Statement: [Lombard Street, hasTrafficControl, seasonal measures to manage tourist congestion]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTrafficControl
Context triple: [Lombard Street, hasTrafficControl, seasonal measures to manage tourist congestion]
  • A. hasTrafficDirection
    Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
  • B. hasSpeedLimit
    Indicates that a specified maximum allowable speed is imposed on the associated entity or context.
  • C. fareControl
    Indicates that an entity is responsible for monitoring, enforcing, or managing payment of fares for access to a service or facility.
  • D. hasLanes
    Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
  • E. hasEntranceControl
    Indicates that an entity implements or is subject to mechanisms that regulate or control access to its entrance.
  • 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_69a493309df48190a327f748e88049a6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49df34abc8190a578c8c2ab3d28e4 completed March 1, 2026, 8:13 p.m.
PD Predicate disambiguation batch_69a49cf8fc1c81908a9c7df552aa1a59 completed March 1, 2026, 8:09 p.m.
PDg Predicate description generation batch_69a49def31ec81909dc53e70f4a36eda completed March 1, 2026, 8:13 p.m.
Created at: March 1, 2026, 7:35 p.m.