Triple

T16764473
Position Surface form Disambiguated ID Type / Status
Subject Prague 1 E407427 entity
Predicate contains P35 FINISHED
Object Municipal House E970558 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: Municipal House | Statement: [Prague 1, contains, Municipal House]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Municipal House
Context triple: [Prague 1, contains, Municipal House]
  • A. Municipal House chosen
    Municipal House is a grand Art Nouveau civic building and concert hall in central Prague, renowned for its ornate architecture and cultural significance.
  • B. Municipal Building
    The Municipal Building, formally known as the Manhattan Municipal Building, is a landmark Beaux-Arts skyscraper in Lower Manhattan that houses New York City government offices.
  • C. Municipal Services Building
    The Municipal Services Building is a major Philadelphia government office complex that houses numerous city administrative departments and public services.
  • D. Neues Rathaus
    Neues Rathaus is Munich’s grand neo-Gothic town hall on Marienplatz, famous for its ornate façade and the Glockenspiel clock tower.
  • E. The Town Hall
    The Town Hall is a historic performance venue in Midtown Manhattan, New York City, renowned for its concerts, lectures, and cultural events.
  • 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.