Triple

T19309581
Position Surface form Disambiguated ID Type / Status
Subject Public Law 90-321 E482929 entity
Predicate hasShortName P1354 FINISHED
Object TILA NE NERFINISHED

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: TILA | Statement: [Public Law 90-321, hasShortName, TILA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TILA
Context triple: [Public Law 90-321, hasShortName, TILA]
  • A. TILA chosen
    TILA is a U.S. federal law that requires lenders to clearly disclose key terms and costs of consumer credit to promote informed borrowing and protect consumers from unfair lending practices.
  • B. Tilakkam
    Tilakkam is a small island that forms part of the Kalpeni atoll in the Lakshadweep archipelago of India.
  • C. Til
    Til is the first name of Til Schweiger, a prominent German actor, filmmaker, and producer known for his roles in both German cinema and international films.
  • D. Tala
    Tala is a town in Maharashtra, India, situated within the Raigad district and known for its rural setting and local administrative significance.
  • E. Tala
    Tala is a young Filipino girl who appears as a guiding spiritual figure in Mitch Albom’s novel "The Five People You Meet in Heaven," helping the protagonist understand the hidden impact of his life and actions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e604cc62e08190b5ba5dfc44efdc5c completed April 20, 2026, 10:49 a.m.
Created at: April 10, 2026, 1:32 p.m.