Triple

T30449155
Position Surface form Disambiguated ID Type / Status
Subject Libya–United States relations E774660 entity
Predicate legalAgreementIssue P17694 FINISHED
Object compensation for terrorism‑related claims 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: compensation for terrorism‑related claims | Statement: [Libya–United States relations, legalAgreementIssue, compensation for terrorism‑related claims]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalAgreementIssue
Context triple: [Libya–United States relations, legalAgreementIssue, compensation for terrorism‑related claims]
  • A. legalAgreement
    Indicates a formal, legally binding arrangement or contract that defines rights, obligations, or terms agreed upon between parties.
  • B. legalContent
    Indicates that the associated material complies with applicable laws and regulations and is permitted for use, distribution, or display.
  • C. mainLegalIssue
    Indicates the primary legal question or dispute that is central to a case or legal matter.
  • D. legalElement
    Indicates that something is a constituent part or component required or recognized within a legal framework, rule, or process.
  • E. treatyOrLegalIssue chosen
    Indicates a formal agreement, dispute, or matter governed by treaties or legal frameworks between parties.
  • 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_69f22493ef9c8190ae8c2afcb7f994c8 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69fe0d165a48819098b854318a50d76c completed May 8, 2026, 4:19 p.m.
PD Predicate disambiguation batch_69fe0931002481908a95b34f95e9f64e completed May 8, 2026, 4:02 p.m.
Created at: April 29, 2026, 8:09 p.m.