Triple

T12883113
Position Surface form Disambiguated ID Type / Status
Subject Porto Metro E308152 entity
Predicate hasRollingStock P1305 FINISHED
Object Eurotram E341678 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: Eurotram | Statement: [Porto Metro, hasRollingStock, Eurotram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurotram
Context triple: [Porto Metro, hasRollingStock, Eurotram]
  • A. Alstom Eurotram chosen
    The Alstom Eurotram is a distinctive low-floor light rail vehicle known for its sleek, modern design and panoramic windows, widely used on urban tram networks in Europe.
  • B. X'Trapolis EMU
    The X'Trapolis EMU is a modern electric multiple unit train used for suburban passenger services on Melbourne’s metropolitan rail network.
  • C. Francilien EMU
    The Francilien EMU is a modern electric multiple-unit train used for suburban and regional passenger services in the Île-de-France (Greater Paris) area.
  • D. Alstom Citadis tram
    The Alstom Citadis tram is a family of modern low-floor light rail vehicles widely used in urban tram networks around the world.
  • E. TGV Sud-Est trainset
    The TGV Sud-Est trainset is the original high-speed electric multiple unit used on France’s pioneering TGV services, known for inaugurating high-speed rail in the country in the early 1980s.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fd15888190baf90fc30f2a3e25 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a5556fe081909ada9d491b21b17b completed May 3, 2026, 1:31 a.m.
Created at: April 9, 2026, 5:39 p.m.