Triple

T37938652
Position Surface form Disambiguated ID Type / Status
Subject Builth Road railway station E946418 entity
Predicate fareZone P844 FINISHED
Object Transport for Wales rural zone
The Transport for Wales rural zone is a designated fare area covering rail services in sparsely populated parts of Wales, offering simplified ticketing and pricing for rural train journeys.
E2249701 NE 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: Transport for Wales rural zone | Statement: [Builth Road railway station, fareZone, Transport for Wales rural zone]
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: Transport for Wales rural zone
Triple: [Builth Road railway station, fareZone, Transport for Wales rural zone]
Generated description
The Transport for Wales rural zone is a designated fare area covering rail services in sparsely populated parts of Wales, offering simplified ticketing and pricing for rural train journeys.

Provenance (5 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_69f76ef531ac8190ae6d99e5786e76ec completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd9e2fac8190a47daa6180a37fd2 completed May 6, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4117f3409c8190952967c5ef4892ef completed June 28, 2026, 12:47 p.m.
NEDg Description generation batch_6a4118a395b8819080fe072ef24f41b3 completed June 28, 2026, 12:50 p.m.
NED2 Entity disambiguation (via description) batch_6a4119cd78bc8190b4f84646eea2ec12 completed June 28, 2026, 12:55 p.m.
Created at: May 3, 2026, 4:20 p.m.