Triple

T1553955
Position Surface form Disambiguated ID Type / Status
Subject Troy, New York E33157 entity
Predicate nickname P55 FINISHED
Object Collar City E61072 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: Collar City | Statement: [Troy, New York, nickname, Collar City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Collar City
Context triple: [Troy, New York, nickname, Collar City]
  • A. Collar City chosen
    Collar City is the nickname for Troy, New York, historically known as a major center of shirt-collar and textile manufacturing.
  • B. The Magic City
    The Magic City is a nickname for Birmingham, Alabama, highlighting its rapid growth during the late 19th and early 20th centuries as an industrial and economic center.
  • C. Gateway City
    Gateway City is a nickname for St. Louis, Missouri, highlighting its historic role as a major entry point to the American West.
  • D. River City
    River City is a popular nickname for Sacramento, California, highlighting the city’s close connection to the nearby American and Sacramento Rivers.
  • E. River City
    River City is a popular nickname for Wuhan, a major central Chinese metropolis known for its location at the confluence of the Yangtze and Han rivers.
  • 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_69a885ee6db8819099502bc5ce8af881 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9086dec008190b5fcf0f2256a581d completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad30a504a881909b01fc27e0b879e7 completed March 8, 2026, 8:17 a.m.
Created at: March 4, 2026, 7:27 p.m.