Triple

T16764480
Position Surface form Disambiguated ID Type / Status
Subject Prague 1 E407427 entity
Predicate contains P35 FINISHED
Object Na Příkopě Street E1192867 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: Na Příkopě Street | Statement: [Prague 1, contains, Na Příkopě Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Na Příkopě Street
Context triple: [Prague 1, contains, Na Příkopě Street]
  • A. Na Příkopě Street chosen
    Na Příkopě Street is a major historic and commercial boulevard in central Prague, known for its upscale shops, offices, and role as one of the city’s main shopping streets.
  • B. Znamenka Street
    Znamenka Street is a historic central street in Moscow, Russia, known for its governmental buildings and proximity to major landmarks like the Kremlin.
  • C. Himmel Street
    Himmel Street is the fictional working-class German street in the town of Molching where much of Markus Zusak’s novel "The Book Thief" takes place.
  • D. Prechistenka Street
    Prechistenka Street is a historic and architecturally significant street in central Moscow, known for its 18th–19th century mansions and cultural landmarks.
  • E. Široká Street
    Široká Street is a historic thoroughfare in Prague’s former Jewish Quarter, known for its proximity to major synagogues and Jewish heritage sites.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3abef492c8190880d3b39c3641eed completed April 18, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a52ff9d481909675c7e1f81191dc completed May 10, 2026, 3:33 p.m.
Created at: April 10, 2026, 5:21 a.m.