Triple

T4355547
Position Surface form Disambiguated ID Type / Status
Subject Talladega Superspeedway E98138 entity
Predicate turnBanking P55733 FINISHED
Object approximately 33 degrees 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: approximately 33 degrees | Statement: [Talladega Superspeedway, turnBanking, approximately 33 degrees]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: turnBanking
Context triple: [Talladega Superspeedway, turnBanking, approximately 33 degrees]
  • A. hasBankingInTurns
    Indicates that an entity participates in banking activities that occur in discrete, alternating turns rather than continuously.
  • B. bankingInTurns
    Indicates that entities are taking alternating roles or actions in a banking-related context, with each one acting in turn rather than simultaneously.
  • C. offersOnlineBanking
    Indicates that a financial institution provides banking services that customers can access and perform over the internet.
  • D. banking
    Indicates that an entity provides or engages in financial services such as holding deposits, managing accounts, or facilitating monetary transactions for another entity.
  • E. transferType
    Indicates the specific method or category of how something is transferred from one entity to another.
  • 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_69b3454965f881908c41190bb22f0e4b completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351c5773481908446d84897e7a533 completed March 12, 2026, 11:52 p.m.
PD Predicate disambiguation batch_69b34f51ed7c8190b7bf5f44b56b730d completed March 12, 2026, 11:42 p.m.
PDg Predicate description generation batch_69b34ff654308190b9717526120d80d3 completed March 12, 2026, 11:44 p.m.
Created at: March 12, 2026, 11:16 p.m.