Triple

T7928003
Position Surface form Disambiguated ID Type / Status
Subject Jonathan B. Postel E184115 entity
Predicate familyName P18 FINISHED
Object Postel E124645 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: Postel | Statement: [Jonathan B. Postel, familyName, Postel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Postel
Context triple: [Jonathan B. Postel, familyName, Postel]
  • A. Postel chosen
    Postel is a surname most prominently associated with Jon Postel, a pioneering computer scientist and key architect of the early Internet.
  • B. David Finfer
    David Finfer was an American film editor known for his work on a wide range of Hollywood movies across several decades.
  • C. Ray Tomlinson
    Ray Tomlinson was an American computer programmer best known for inventing networked email and introducing the use of the "@" symbol in email addresses.
  • D. Jonathan B. Postel
    Jonathan B. Postel was an American computer scientist and Internet pioneer best known for his foundational role in developing and administering core Internet protocols and standards.
  • E. Paul Postal
    Paul Postal is an American linguist known for his influential work in generative grammar and syntax, including early contributions to transformational grammar and critiques of mainstream linguistic theory.
  • 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_69ca828fe7bc819090f52c88dcd72183 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aafdb5c8190b7f2ce5349305f78 completed March 31, 2026, 3:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5bfd08e88190bc6b2d77a148ae57 completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:07 p.m.