Triple

T9321990
Position Surface form Disambiguated ID Type / Status
Subject Jonathan Hunt E224289 entity
Predicate name P16 FINISHED
Object Jonathan Hunt E224289 NE 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: Jonathan Hunt | Statement: [Jonathan Hunt, name, Jonathan Hunt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonathan Hunt
Context triple: [Jonathan Hunt, name, Jonathan Hunt]
  • A. Jonathan Hunt chosen
    Jonathan Hunt was a prominent early 19th-century American politician and lawyer from Vermont who served multiple terms in the U.S. House of Representatives.
  • B. Jonathan J. Hunt
    Jonathan J. Hunt is a researcher in machine learning and control who is credited with introducing the Deep Deterministic Policy Gradient (DDPG) algorithm for continuous action reinforcement learning.
  • C. Dan Hunt
    Dan Hunt is an American soccer executive and co-owner of FC Dallas, known for leading the Major League Soccer club founded by his family.
  • D. Ian Hallard
    Ian Hallard is a British actor and writer known for his work in television, theatre, and radio, as well as for his collaborations with his husband, writer-actor Mark Gatiss.
  • E. Christopher Gunning
    Christopher Gunning was a British composer best known for his film and television scores, including the iconic theme for the detective series "Poirot."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca8426d48481909596360f7791c7dd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd36f2bd288190bb1556a88d9e90f3 completed April 1, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14bd5c89081909533dbfc9f82016d completed April 4, 2026, 5:35 p.m.
Created at: March 30, 2026, 7:38 p.m.