Triple

T4276887
Position Surface form Disambiguated ID Type / Status
Subject tiangolo E97064 entity
Predicate notableProject P4 FINISHED
Object Typer
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.
 E426660 NE FINISHED

How this triple was built (4 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: [tiangolo, notableProject, Typer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Typer
Context triple: [tiangolo, notableProject, Typer]
  • A. Ty
    Ty is the first name of American musician and songwriter Ty Segall, known for his prolific work in garage and psychedelic rock.
  • B. Tukker
    Tukker is a given name or surname that functions as a variant spelling of the name Tucker.
  • C. Tay
    The Tay is the longest river in Scotland, flowing through Perth and Dundee before emptying into the North Sea.
  • D. Tayasan
    Tayasan is a coastal municipality in the province of Negros Oriental in the Philippines, known for its rural communities and agricultural economy.
  • E. Tyro
    Tyro is a figure from Greek mythology, known as the mother of the twins Pelias and Neleus by the god Poseidon.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Typer
Triple: [tiangolo, notableProject, Typer]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Typer
Target entity description: 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.
  • A. Ty
    Ty is the first name of American musician and songwriter Ty Segall, known for his prolific work in garage and psychedelic rock.
  • B. Tukker
    Tukker is a given name or surname that functions as a variant spelling of the name Tucker.
  • C. Tay
    The Tay is the longest river in Scotland, flowing through Perth and Dundee before emptying into the North Sea.
  • D. Tayasan
    Tayasan is a coastal municipality in the province of Negros Oriental in the Philippines, known for its rural communities and agricultural economy.
  • E. Tyro
    Tyro is a figure from Greek mythology, known as the mother of the twins Pelias and Neleus by the god Poseidon.
  • F. None of above. chosen

Provenance (5 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501d677481909e7416a1d2b0008c completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b3b52c8190ae7c05448faf5558 completed March 14, 2026, 7:32 p.m.
NEDg Description generation batch_69b5b95083088190b0c993fa2fbc954c completed March 14, 2026, 7:38 p.m.
NED2 Entity disambiguation (via description) batch_69b5b9b8afcc8190822cfd560d064590 completed March 14, 2026, 7:40 p.m.
Created at: March 12, 2026, 11:07 p.m.