Triple

T27653273
Position Surface form Disambiguated ID Type / Status
Subject Stansstad E696920 entity
Predicate hasLakeShipping P175036 FINISHED
Object Lake Lucerne Navigation Company
The Lake Lucerne Navigation Company is a Swiss transport operator that runs passenger and excursion boat services on Lake Lucerne, including historic paddle steamers and modern vessels.
 E1784081 NE FINISHED

How this triple was built (3 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: Lake Lucerne Navigation Company | Statement: [Stansstad, hasLakeShipping, Lake Lucerne Navigation Company]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lake Lucerne Navigation Company
Triple: [Stansstad, hasLakeShipping, Lake Lucerne Navigation Company]
Generated description
The Lake Lucerne Navigation Company is a Swiss transport operator that runs passenger and excursion boat services on Lake Lucerne, including historic paddle steamers and modern vessels.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasLakeShipping
Context triple: [Stansstad, hasLakeShipping, Lake Lucerne Navigation Company]
  • A. hasLakePort
    Indicates that a place or region possesses a port or harbor facility located on a lake.
  • B. hasShippingLaneType
    Indicates the specific category or type of shipping lane associated with a given route or area.
  • C. hasWharf
    Indicates that one place or facility possesses or is equipped with a wharf for docking boats or ships.
  • D. hasLakes
    Indicates that one entity possesses, contains, or is characterized by the presence of one or more lakes.
  • E. isInlandWaterwayTransportHubFor chosen
    Indicates that a location functions as a central node or hub within an inland waterway network for the transport of goods or passengers.
  • F. None of above.

Provenance (6 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_69ef590abd3c8190834d0193bde12007 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f7c29e1b848190b945c6c6120a5330 completed May 3, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12da99a7088190adae6a011d941654 completed May 24, 2026, 11:01 a.m.
NEDg Description generation batch_6a12db2833688190af921e97c6e5d05d completed May 24, 2026, 11:04 a.m.
NED2 Entity disambiguation (via description) batch_6a12db977df48190b71bce8408b51269 completed May 24, 2026, 11:05 a.m.
PD Predicate disambiguation batch_69f7c1b6e7a881908deb96bedb2713f4 completed May 3, 2026, 9:44 p.m.
Created at: April 27, 2026, 2:33 p.m.