Triple

T10600396
Position Surface form Disambiguated ID Type / Status
Subject Bakhtiari E275728 entity
Predicate hasNotableBearer P458 FINISHED
Object David Bakhtiari E55545 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: David Bakhtiari | Statement: [Bakhtiari, hasNotableBearer, David Bakhtiari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Bakhtiari
Context triple: [Bakhtiari, hasNotableBearer, David Bakhtiari]
  • A. David Bakhtiari chosen
    David Bakhtiari is an American football offensive tackle best known for his Pro Bowl career with the Green Bay Packers in the NFL.
  • B. Behdad Eghbali
    Behdad Eghbali is an American private equity investor and co-founder of Clearlake Capital Group, known for major investments in sports, technology, and industrial companies.
  • C. Darius Alizadeh
    Darius Alizadeh is a character appearing in the James Bond continuation novel "Devil May Care" by Sebastian Faulks.
  • D. Mehdi Hatamian
    Mehdi Hatamian is an electrical engineer and technologist recognized for his influential contributions to high-speed integrated circuits and signal processing, for which he has received major industry honors.
  • E. Zekeria Ebrahimi
    Zekeria Ebrahimi is an Afghan actor best known for his role as the young Amir in the film adaptation of "The Kite Runner."
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6ded52f288190b40288d0acbe009b completed April 8, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b698f308190be8ee1e6bc8481d3 completed April 10, 2026, 9:28 p.m.
Created at: April 8, 2026, 7:30 p.m.