Triple

T8931945
Position Surface form Disambiguated ID Type / Status
Subject Montserrado County E212676 entity
Predicate populationRankInLiberia P86250 FINISHED
Object 1 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: 1 | Statement: [Montserrado County, populationRankInLiberia, 1]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: populationRankInLiberia
Context triple: [Montserrado County, populationRankInLiberia, 1]
  • A. populationRankInLuxembourg
    Indicates the relative position of a place in Luxembourg when ordered by the size of its population.
  • B. countryRanking
    Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
  • C. populationRank
    Indicates the relative position of an entity in an ordered list based on the size of its population.
  • D. countryRankingContext
    Indicates the contextual framework or criteria under which a country's ranking is determined or interpreted.
  • E. populationRankInSudan
    Indicates the relative position of an entity in terms of population size compared to other entities within Sudan.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc668e5c108190b08f9cd6b4fd4a8b completed April 1, 2026, 12:27 a.m.
PD Predicate disambiguation batch_69cc5ed3286c8190a21de2ee11f2639f completed March 31, 2026, 11:54 p.m.
PDg Predicate description generation batch_69cc608331f88190bcb500ff63527f8a completed April 1, 2026, 12:02 a.m.
Created at: March 30, 2026, 6:57 p.m.