Triple

T1536778
Position Surface form Disambiguated ID Type / Status
Subject Indiana E32567 entity
Predicate hasAreaRankInUS P1891 FINISHED
Object 38 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: 38 | Statement: [Indiana, hasAreaRankInUS, 38]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAreaRankInUS
Context triple: [Indiana, hasAreaRankInUS, 38]
  • A. areaRankInUS chosen
    Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
  • B. areaRankingInContiguousUS
    Indicates the relative position of an entity when U.S. states are ordered by area, considering only those in the contiguous United States.
  • C. isInMetropolitanAreaRank
    Indicates that one metropolitan area holds a specific rank or position relative to others based on a defined metropolitan-area-related criterion (such as size, population, or importance).
  • D. areaRank
    Indicates the relative ordering or position of an entity based on the size of its area compared to others.
  • E. rankByPopulationInUS
    Indicates the relative ordering of entities based on the size of their populations within the United States.
  • F. None of above.

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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a915f323bc8190aa757142c225e0ae completed March 5, 2026, 5:34 a.m.
PD Predicate disambiguation batch_69a907b046448190be8ea4d7b20255f7 completed March 5, 2026, 4:33 a.m.
Created at: March 4, 2026, 7:26 p.m.