Triple

T585356
Position Surface form Disambiguated ID Type / Status
Subject Turin E15144 entity
Predicate hasRailwayStation P918 FINISHED
Object Torino Porta Susa
Torino Porta Susa is a major high-speed and regional railway hub in Turin, Italy, serving as one of the city’s principal train stations.
 E74224 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: Torino Porta Susa | Statement: [Turin, hasRailwayStation, Torino Porta Susa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Torino Porta Susa
Context triple: [Turin, hasRailwayStation, Torino Porta Susa]
  • A. Torino Porta Nuova
    Torino Porta Nuova is the main railway station in Turin, Italy, serving as a major national and international transport hub.
  • B. Turin
    Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
  • C. Bardonecchia
    Bardonecchia is an alpine town in northwestern Italy known as a ski resort and transport hub near the French border in the Susa Valley.
  • D. Tremezzo
    Tremezzo is a picturesque lakeside town in northern Italy’s Lombardy region, renowned for its historic villas, gardens, and scenic views over Lake Como.
  • E. Cernobbio
    Cernobbio is a picturesque town in northern Italy known for its lakeside villas and scenic location on the shores of Lake Como.
  • 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: Torino Porta Susa
Triple: [Turin, hasRailwayStation, Torino Porta Susa]
Generated description
Torino Porta Susa is a major high-speed and regional railway hub in Turin, Italy, serving as one of the city’s principal train stations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Torino Porta Susa
Target entity description: Torino Porta Susa is a major high-speed and regional railway hub in Turin, Italy, serving as one of the city’s principal train stations.
  • A. Torino Porta Nuova
    Torino Porta Nuova is the main railway station in Turin, Italy, serving as a major national and international transport hub.
  • B. Turin
    Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
  • C. Bardonecchia
    Bardonecchia is an alpine town in northwestern Italy known as a ski resort and transport hub near the French border in the Susa Valley.
  • D. Tremezzo
    Tremezzo is a picturesque lakeside town in northern Italy’s Lombardy region, renowned for its historic villas, gardens, and scenic views over Lake Como.
  • E. Cernobbio
    Cernobbio is a picturesque town in northern Italy known for its lakeside villas and scenic location on the shores of Lake Como.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b9874c88190bd1e08d4689ea124 completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5155210dc8190bad32b49703641e2 completed March 2, 2026, 4:42 a.m.
NEDg Description generation batch_69a51788f870819099271dcb41ee4bda completed March 2, 2026, 4:52 a.m.
NED2 Entity disambiguation (via description) batch_69a51846caa481909a61fa29a44b7470 completed March 2, 2026, 4:55 a.m.
Created at: March 1, 2026, 7:33 p.m.