Triple

T14729326
Position Surface form Disambiguated ID Type / Status
Subject Downtown Frederick E346028 entity
Predicate hasLandmark P105 FINISHED
Object Frederick City Hall E348849 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: Frederick City Hall | Statement: [Downtown Frederick, hasLandmark, Frederick City Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frederick City Hall
Context triple: [Downtown Frederick, hasLandmark, Frederick City Hall]
  • A. Frederick City Hall chosen
    Frederick City Hall is the historic municipal building in Frederick, Maryland that serves as the center of city government and administration.
  • B. Newton City Hall
    Newton City Hall is the main municipal government building and administrative center for the city of Newton, Massachusetts.
  • C. Jackson City Hall
    Jackson City Hall is the primary municipal government building in Jackson, serving as the central location for city administration and public meetings.
  • D. Cornelius City Hall
    Cornelius City Hall is the primary municipal government building serving the city of Cornelius in Washington County, Oregon.
  • E. Alabaster City Hall
    Alabaster City Hall is the primary municipal government building and administrative center for the city of Alabaster, Alabama.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec26179688190ba9f3cd045da0e2a completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb87ef7c8190a46f317e5475d40e completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:29 a.m.