Triple

T4549707
Position Surface form Disambiguated ID Type / Status
Subject Sebastián Ramírez E110131 entity
Predicate notableWork P4 FINISHED
Object Typer E426660 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: Typer | Statement: [Sebastián Ramírez, notableWork, Typer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Typer
Context triple: [Sebastián Ramírez, notableWork, Typer]
  • A. Typer chosen
    Typer is a modern, user-friendly Python library for building command-line interfaces, created by Sebastián Ramírez (tiangolo), that emphasizes type hints and automatic documentation.
  • B. typer
    Typer is a modern, user-friendly Python library for building command-line interfaces, created by Sebastián Ramírez (tiangolo), the author of FastAPI.
  • C. Ty
    Ty is the first name of American musician and songwriter Ty Segall, known for his prolific work in garage and psychedelic rock.
  • D. Tukker
    Tukker is a given name or surname that functions as a variant spelling of the name Tucker.
  • E. Tay
    The Tay is the longest river in Scotland, flowing through Perth and Dundee before emptying into the North Sea.
  • 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_69bd4412524c8190be5bcc9ddee91848 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57f3f8348190868e274ac4df87ce completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdb94cab408190956ef333aa810a3b completed March 20, 2026, 9:17 p.m.
Created at: March 20, 2026, 1:05 p.m.