Triple

T12771664
Position Surface form Disambiguated ID Type / Status
Subject Linha da Beira Baixa E305260 entity
Predicate hasTerminus P388 FINISHED
Object Guarda railway station E735220 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: Guarda railway station | Statement: [Linha da Beira Baixa, hasTerminus, Guarda railway station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guarda railway station
Context triple: [Linha da Beira Baixa, hasTerminus, Guarda railway station]
  • A. Guarda railway station chosen
    Guarda railway station is the main rail transport hub serving the city of Guarda in Portugal, connecting it to regional and national rail networks.
  • B. Garding railway station
    Garding railway station is a local train stop serving the town of Garding in the Nordfriesland district of Schleswig-Holstein, Germany.
  • C. Trang railway station
    Trang railway station is the main railway hub serving the town and province of Trang in southern Thailand, connecting the region to the national rail network.
  • D. Bro railway station
    Bro railway station is a local commuter rail stop in Bro, Sweden, serving as part of the Stockholm commuter rail network.
  • E. Landhi Railway Station
    Landhi Railway Station is a major railway hub in the Landhi area of Karachi, Pakistan, serving as an important stop for intercity and commuter train services.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df5b68481908a5d40516b09be52 completed April 10, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684fcd4b48190ab610efffcbd1546 completed May 2, 2026, 11:13 p.m.
Created at: April 9, 2026, 5:28 p.m.