Triple

T10769709
Position Surface form Disambiguated ID Type / Status
Subject Line 5 (Barcelona Metro) E254041 entity
Predicate connectsStation P845 FINISHED
Object Horta
Horta is a Barcelona Metro station serving the Horta neighborhood in the city’s northeastern district.
E886180 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: Horta | Statement: [Line 5 (Barcelona Metro), connectsStation, Horta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Horta
Context triple: [Line 5 (Barcelona Metro), connectsStation, Horta]
  • A. Horta
    Horta is a coastal city on the island of Faial in the Azores, known for its historic transatlantic harbor and vibrant marina frequented by ocean-crossing yachts.
  • B. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • C. Figueira da Horta
    Figueira da Horta is a small village located on the island of Maio in Cape Verde.
  • D. Sernancelhe
    Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
  • E. Odivelas
    Odivelas is a suburban city and municipality in the Lisbon metropolitan area of Portugal, known for its residential character and proximity to the capital.
  • 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: Horta
Triple: [Line 5 (Barcelona Metro), connectsStation, Horta]
Generated description
Horta is a Barcelona Metro station serving the Horta neighborhood in the city’s northeastern district.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Horta
Target entity description: Horta is a Barcelona Metro station serving the Horta neighborhood in the city’s northeastern district.
  • A. Horta
    Horta is a coastal city on the island of Faial in the Azores, known for its historic transatlantic harbor and vibrant marina frequented by ocean-crossing yachts.
  • B. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • C. Figueira da Horta
    Figueira da Horta is a small village located on the island of Maio in Cape Verde.
  • D. Sernancelhe
    Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
  • E. Odivelas
    Odivelas is a suburban city and municipality in the Lisbon metropolitan area of Portugal, known for its residential character and proximity to the capital.
  • 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_69de55cbbecc81908c2ddf2739ce7ffe completed April 14, 2026, 2:57 p.m.
NEDg Description generation batch_69de5eacae148190b7ca2da87427572e completed April 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69de6397ff688190b6788489895a5360 completed April 14, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:16 p.m.