Triple

T10400140
Position Surface form Disambiguated ID Type / Status
Subject Welsh Highland Railway E245123 entity
Predicate hasDepot P2413 FINISHED
Object Dinas depot
Dinas depot is a maintenance and storage facility serving the Welsh Highland Railway in North Wales.
E861155 NE FINISHED

How this triple was built (4 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: Dinas depot | Statement: [Welsh Highland Railway, hasDepot, Dinas depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dinas depot
Context triple: [Welsh Highland Railway, hasDepot, Dinas depot]
  • A. Pajura depot
    Pajura depot is a maintenance and storage facility serving the Bucharest Metro system in Romania.
  • B. Ansim Depot
    Ansim Depot is a maintenance and storage facility serving the Daegu Metro system in Daegu, South Korea.
  • C. Carnide depot
    Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • D. Militari depot
    Militari depot is a major maintenance and storage facility serving the Bucharest Metro system in Bucharest, Romania.
  • E. Caolu Depot
    Caolu Depot is a maintenance and storage facility serving Shanghai Metro’s Line 9 in the Pudong area.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Dinas depot
Triple: [Welsh Highland Railway, hasDepot, Dinas depot]
Generated description
Dinas depot is a maintenance and storage facility serving the Welsh Highland Railway in North Wales.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dinas depot
Target entity description: Dinas depot is a maintenance and storage facility serving the Welsh Highland Railway in North Wales.
  • A. Pajura depot
    Pajura depot is a maintenance and storage facility serving the Bucharest Metro system in Romania.
  • B. Ansim Depot
    Ansim Depot is a maintenance and storage facility serving the Daegu Metro system in Daegu, South Korea.
  • C. Carnide depot
    Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • D. Militari depot
    Militari depot is a major maintenance and storage facility serving the Bucharest Metro system in Bucharest, Romania.
  • E. Caolu Depot
    Caolu Depot is a maintenance and storage facility serving Shanghai Metro’s Line 9 in the Pudong area.
  • F. None of above. chosen

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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9d2e8488190b2bb8f8509903804 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fbc759a08190be677bf5458af0c8 completed April 9, 2026, 7:19 p.m.
NEDg Description generation batch_69d81c40dc6081908cc186ee6cd0814e completed April 9, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69d8277fbf0881908a1e16d6c07886e6 completed April 9, 2026, 10:26 p.m.
Created at: April 6, 2026, 12:07 p.m.