Triple

T27086803
Position Surface form Disambiguated ID Type / Status
Subject Lancashire wrestling E686056 entity
Predicate legalTechniques P183482 FINISHED
Object leg attacks 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: leg attacks | Statement: [Lancashire wrestling, legalTechniques, leg attacks]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalTechniques
Context triple: [Lancashire wrestling, legalTechniques, leg attacks]
  • A. legalTool
    Indicates a relationship where something functions as a legal instrument, mechanism, or means used to achieve or regulate a legal purpose or outcome.
  • B. legalPractice
    Indicates a relationship where an entity engages in or is associated with the professional provision of legal services or the practice of law.
  • C. legalFeature
    Indicates that something possesses a specific legal characteristic, status, or attribute relevant to laws or regulations.
  • D. legalMatters
    Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
  • E. legalRepresentation
    Indicates that one entity formally acts on behalf of another in legal matters, such as providing counsel, advocacy, or defense within a legal system.
  • 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_69ef148940ec819097b5c20fbfbf7c81 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f7a01efcc08190bba489a9099b8684 completed May 3, 2026, 7:21 p.m.
PD Predicate disambiguation batch_69f79e4888248190be2f63cdfb5cd7b7 completed May 3, 2026, 7:13 p.m.
PDg Predicate description generation batch_69f79f477c4c8190a35cb6d87b1dcbd1 completed May 3, 2026, 7:17 p.m.
Created at: April 27, 2026, 8:38 a.m.