Triple

T6496468
Position Surface form Disambiguated ID Type / Status
Subject Line 5 (Madrid Metro) E148172 entity
Predicate formerTerminus P388 FINISHED
Object Callao E533335 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: Callao | Statement: [Line 5 (Madrid Metro), formerTerminus, Callao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Callao
Context triple: [Line 5 (Madrid Metro), formerTerminus, Callao]
  • A. Callao
    Callao is Peru’s chief seaport and a major coastal city adjacent to Lima, serving as the country’s principal gateway for maritime trade.
  • B. Callao chosen
    Callao is a central Madrid Metro station located in the busy commercial and entertainment hub around Plaza del Callao in the city center.
  • C. Lima
    Lima is the capital and largest city of Peru, known as a major political, economic, and cultural center on South America's Pacific coast.
  • D. Miraflores
    Miraflores is an upscale coastal district of Lima, Peru, known for its shopping, dining, nightlife, and cliffside views over the Pacific Ocean.
  • E. Trujillo
    Trujillo is a historic Spanish town in the region of Extremadura, renowned for its well-preserved medieval architecture and impressive main square.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06aba8f04819080b291baf79c42d5 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d506900c819093e9528426875942 completed March 27, 2026, 7:05 p.m.
Created at: March 22, 2026, 4:53 p.m.