Triple

T9943981
Position Surface form Disambiguated ID Type / Status
Subject Lehigh Valley region E194154 entity
Predicate populationRankInPennsylvania P91281 FINISHED
Object third-largest metropolitan area in Pennsylvania 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: third-largest metropolitan area in Pennsylvania | Statement: [Lehigh Valley region, populationRankInPennsylvania, third-largest metropolitan area in Pennsylvania]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: populationRankInPennsylvania
Context triple: [Lehigh Valley region, populationRankInPennsylvania, third-largest metropolitan area in Pennsylvania]
  • A. rankByPopulationInUnitedStates
    Indicates the relative ordering of entities based on their population size within the United States.
  • B. rankByPopulationInUS
    Indicates the relative ordering of entities based on the size of their populations within the United States.
  • C. provinceRank
    Indicates the relative position or level assigned to a province within an ordered ranking or hierarchy.
  • D. populationRankInOhio
    Indicates the relative ranking of an entity’s population size compared to other entities within the state of Ohio.
  • E. populationRankInWashington
    Indicates the relative ranking of an entity’s population size compared to other entities within Washington.
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb613fbb48190b82a06987310cc96 completed April 2, 2026, 12:19 a.m.
PD Predicate disambiguation batch_69cd1d9428cc81909b4b4938566d78a7 completed April 1, 2026, 1:28 p.m.
PDg Predicate description generation batch_69cd358386f48190833c862b5b8c04b2 completed April 1, 2026, 3:10 p.m.
Created at: March 30, 2026, 8:45 p.m.