Triple

T9999315
Position Surface form Disambiguated ID Type / Status
Subject Kris Paronto E197282 entity
Predicate coAuthor P398 FINISHED
Object Mark Geist E197308 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: Mark Geist | Statement: [Kris Paronto, coAuthor, Mark Geist]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Geist
Context triple: [Kris Paronto, coAuthor, Mark Geist]
  • A. Mark Geist chosen
    Mark Geist is a former U.S. Marine and security contractor best known as one of the Benghazi attack survivors whose actions were depicted in the book and film "13 Hours."
  • B. Jon Oberheide
    Jon Oberheide is a cybersecurity entrepreneur and researcher best known as the co-founder and former CTO of Duo Security, a leading multi-factor authentication and zero-trust security company.
  • C. Michael Grunst
    Michael Grunst is a German local politician who serves as the borough mayor of Berlin’s Lichtenberg district.
  • D. Michael Hecht
    Michael Hecht is the birth name of Michael Howard, a British Conservative politician who served as Leader of the Opposition and Home Secretary.
  • E. Michael Hecht
    Michael Hecht is a scientist best known for leading NASA’s MOXIE experiment on the Perseverance rover, which demonstrates in-situ oxygen production on Mars.
  • 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_69ca82f3b61c81908ecc2c1c96dbc2e4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdcc8dc9c081909b6d20909ada09cf completed April 2, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2584bd6cc8190841353847dd2f00c completed April 5, 2026, 12:40 p.m.
Created at: March 30, 2026, 8:51 p.m.