Triple

T8749773
Position Surface form Disambiguated ID Type / Status
Subject Knickerbocker group E207926 entity
Predicate literaryCenter P85173 FINISHED
Object Manhattan E8787 NE FINISHED

How this triple was built (3 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: Manhattan | Statement: [Knickerbocker group, literaryCenter, Manhattan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manhattan
Context triple: [Knickerbocker group, literaryCenter, Manhattan]
  • A. Manhattan chosen
    Manhattan is the densely populated, iconic core borough of New York City, known for its skyscrapers, cultural institutions, and role as a global financial and media center.
  • B. Manhattan
    The Manhattan is a classic whiskey-based cocktail, traditionally made with rye or bourbon, sweet vermouth, and bitters, and typically served stirred and garnished with a cherry.
  • C. New York City
    New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
  • D. NYC
    NYC is a historic American railroad company that operated major passenger and freight services across the northeastern and midwestern United States.
  • E. Brooklyn
    Brooklyn is a populous and culturally diverse borough of New York City known for its distinct neighborhoods, arts scene, and iconic landmarks like the Brooklyn Bridge.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: literaryCenter
Context triple: [Knickerbocker group, literaryCenter, Manhattan]
  • A. literaryCollection
    Indicates that one entity is a collection or compilation of literary works that includes or is associated with the other entity.
  • B. inLiterature
    Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
  • C. literarySource
    Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
  • D. literarySubject
    Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
  • E. literaryUnit
    Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
  • F. None of above. chosen

Provenance (5 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_69ca835bb2bc819084bb5906cb6ef7f8 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5da5d474819084ae81d21a5089fa completed March 31, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfd069faa481908db58399fe8f72f1 completed April 3, 2026, 2:36 p.m.
PD Predicate disambiguation batch_69cc5c160dac8190b4aeb4bf0529de52 completed March 31, 2026, 11:43 p.m.
PDg Predicate description generation batch_69cc5cfddef48190aee764ee7b25bae9 completed March 31, 2026, 11:47 p.m.
Created at: March 30, 2026, 6:39 p.m.