Triple

T37542261
Position Surface form Disambiguated ID Type / Status
Subject Swarzewo E933359 entity
Predicate hasRailwayStop P726 FINISHED
Object Swarzewo railway stop
Swarzewo railway stop is a small passenger rail station serving the village of Swarzewo in northern Poland, providing local and regional train connections.
 E2231990 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: Swarzewo railway stop | Statement: [Swarzewo, hasRailwayStop, Swarzewo railway stop]
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: Swarzewo railway stop
Triple: [Swarzewo, hasRailwayStop, Swarzewo railway stop]
Generated description
Swarzewo railway stop is a small passenger rail station serving the village of Swarzewo in northern Poland, providing local and regional train connections.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasRailwayStop
Context triple: [Swarzewo, hasRailwayStop, Swarzewo railway stop]
  • A. hasRailwayStation
    Indicates that a place or location is served by, or contains, a railway station.
  • B. hasRailStation chosen
    Indicates that one entity possesses, contains, or is served by a rail station.
  • C. hasRailwayStationRole
    Indicates that an entity holds or is assigned a specific functional role or capacity within the operation or management of a railway station.
  • D. hasRailwayStationOn
    Indicates that a railway station is located on or serves a particular railway line, route, or network segment.
  • E. isRailwayStation
    Indicates that the subject is a railway station, i.e., a facility where trains regularly stop to pick up or drop off passengers and/or freight.
  • 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_69f76ec999288190ae26ec7b6aea7046 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fe066d62b48190867df334039be786 completed May 8, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a409f081d608190a8dd3e3b8393c8a9 completed June 28, 2026, 4:11 a.m.
NEDg Description generation batch_6a409f9eb63c8190866e647770e86bb3 completed June 28, 2026, 4:14 a.m.
NED2 Entity disambiguation (via description) batch_6a40a0aa945c81909a9b8ab5b797d45a completed June 28, 2026, 4:18 a.m.
PD Predicate disambiguation batch_69fe03afde3c8190a5b9b0778d19eb1a completed May 8, 2026, 3:39 p.m.
Created at: May 3, 2026, 4:17 p.m.