Triple

T10769634
Position Surface form Disambiguated ID Type / Status
Subject Line 3 (Barcelona Metro) E254040 entity
Predicate servesStation P839 FINISHED
Object Maria Cristina station
Maria Cristina station is a Barcelona Metro stop located in the Les Corts district, serving passengers on the city's Line 3.
E884804 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: Maria Cristina station | Statement: [Line 3 (Barcelona Metro), servesStation, Maria Cristina station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maria Cristina station
Context triple: [Line 3 (Barcelona Metro), servesStation, Maria Cristina station]
  • A. Carlini Station
    Carlini Station is an Argentine Antarctic research base on King George Island, focused on scientific studies of the polar environment and climate.
  • B. Francisco station
    Francisco station is an elevated Chicago 'L' rapid transit stop on the Brown Line located in the city's Ravenswood Manor neighborhood.
  • C. Bellavista station
    Bellavista station is a passenger rail stop on the Valparaíso Metro system serving the coastal city of Valparaíso, Chile.
  • D. Primos station
    Primos station is a commuter rail stop in Pennsylvania serving the SEPTA Regional Rail network.
  • E. Pío Nono station
    Pío Nono station is a lower terminal of Santiago’s historic funicular railway that provides access to San Cristóbal Hill in Chile.
  • 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: Maria Cristina station
Triple: [Line 3 (Barcelona Metro), servesStation, Maria Cristina station]
Generated description
Maria Cristina station is a Barcelona Metro stop located in the Les Corts district, serving passengers on the city's Line 3.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maria Cristina station
Target entity description: Maria Cristina station is a Barcelona Metro stop located in the Les Corts district, serving passengers on the city's Line 3.
  • A. Carlini Station
    Carlini Station is an Argentine Antarctic research base on King George Island, focused on scientific studies of the polar environment and climate.
  • B. Francisco station
    Francisco station is an elevated Chicago 'L' rapid transit stop on the Brown Line located in the city's Ravenswood Manor neighborhood.
  • C. Bellavista station
    Bellavista station is a passenger rail stop on the Valparaíso Metro system serving the coastal city of Valparaíso, Chile.
  • D. Primos station
    Primos station is a commuter rail stop in Pennsylvania serving the SEPTA Regional Rail network.
  • E. Pío Nono station
    Pío Nono station is a lower terminal of Santiago’s historic funicular railway that provides access to San Cristóbal Hill in Chile.
  • 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d732307fb88190ba1447f68523c58a completed April 9, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69de23798af48190874d7e12c5155913 completed April 14, 2026, 11:22 a.m.
NEDg Description generation batch_69de271fb08c8190a44c547083226fd8 completed April 14, 2026, 11:38 a.m.
NED2 Entity disambiguation (via description) batch_69de2cecc24c8190a240366e0600426a completed April 14, 2026, 12:02 p.m.
Created at: April 8, 2026, 9:16 p.m.