Triple

T16089531
Position Surface form Disambiguated ID Type / Status
Subject Line C (Prague Metro) E390323 entity
Predicate interchangeStation P15892 FINISHED
Object Florenc station E1195190 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: Florenc station | Statement: [Line C (Prague Metro), interchangeStation, Florenc station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florenc station
Context triple: [Line C (Prague Metro), interchangeStation, Florenc station]
  • A. Florenc station chosen
    Florenc station is a major interchange hub in the Prague Metro system, serving as a key transfer point between multiple lines and providing access to the city’s main bus terminal.
  • B. Oriente station
    Oriente station is a major multimodal transport hub in Lisbon, Portugal, serving as a key connection point for trains, metro, buses, and regional services.
  • C. Collblanc station
    Collblanc station is a major Barcelona Metro interchange serving multiple lines and providing access to the city's western districts and nearby Camp Nou stadium.
  • D. Verdaguer station
    Verdaguer station is an interchange stop on the Barcelona Metro network serving the central Eixample district.
  • E. Legarda station
    Legarda station is an elevated rapid transit stop on Manila’s LRT Line 2 serving the Sampaloc area and nearby universities.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1845161908190adca2af94710b2cc completed April 17, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff29bc7408190be09bec1619b599c completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 4:59 a.m.