Triple

T27155425
Position Surface form Disambiguated ID Type / Status
Subject Pennsylvania–Delaware border E682505 entity
Predicate cartographicallyDistinct P161919 FINISHED
Object yes LITERAL 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: yes | Statement: [Pennsylvania–Delaware border, cartographicallyDistinct, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: cartographicallyDistinct
Context triple: [Pennsylvania–Delaware border, cartographicallyDistinct, yes]
  • A. regionallyDistinctFrom
    Indicates that two entities differ from each other in characteristics or classification based on their geographic or regional context.
  • B. geographicalRepresentation
    Indicates that one entity serves as a geographic depiction, model, or mapping of another entity’s location, area, or spatial characteristics.
  • C. cartographicSignificance
    Indicates the importance or relevance of something within the context of mapping or geographic representation.
  • D. geographicOverlap
    Indicates that two geographic areas share at least part of the same physical space or territory.
  • E. geographicallySeparatedFrom
    Indicates that two places or regions are distinct and apart from each other in physical location or geographic space.
  • F. None of above. chosen

Provenance (4 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_69eefaceb2a08190b9659b7f730629f5 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625069a00819096cf4b71a69a3563 completed May 2, 2026, 4:23 p.m.
PD Predicate disambiguation batch_69f61b40f02081909bd9c3ea73249163 completed May 2, 2026, 3:41 p.m.
PDg Predicate description generation batch_69f61fa35ac48190890102c348ed81a0 completed May 2, 2026, 4 p.m.
Created at: April 27, 2026, 9:16 a.m.