Triple

T1635021
Position Surface form Disambiguated ID Type / Status
Subject PGP E35340 entity
Predicate developer P73 FINISHED
Object Phil Zimmermann E141432 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: Phil Zimmermann | Statement: [PGP, developer, Phil Zimmermann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phil Zimmermann
Context triple: [PGP, developer, Phil Zimmermann]
  • A. Phil Zimmermann chosen
    Phil Zimmermann is an American cryptographer best known as the creator of Pretty Good Privacy (PGP), a widely used email encryption software that helped popularize strong cryptography for the public.
  • B. Jim Manzi
    Jim Manzi is an American businessman best known for leading Lotus Development Corporation as its CEO during the height of its success in the software industry.
  • C. Isaac Z. Schlueter
    Isaac Z. Schlueter is a software engineer and entrepreneur best known for founding npm, the widely used package manager for the Node.js ecosystem.
  • D. Christopher Lennertz
    Christopher Lennertz is an American composer best known for his film, television, and video game scores, including work on major comedies, action films, and popular series like Supernatural.
  • E. Jonathan Schwartz
    Jonathan Schwartz is a film producer best known for his work on acclaimed independent movies such as "Like Crazy."
  • 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_69a886036bc081909ff5de16dbe5e8ea completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a1679408190a9faa7b22c388c4b completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad6099979481908e2c506323d546dd completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:28 p.m.