Triple

T4276868
Position Surface form Disambiguated ID Type / Status
Subject tiangolo E97064 entity
Predicate associatedWith P37 FINISHED
Object FastAPI community E17658 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: FastAPI community | Statement: [tiangolo, associatedWith, FastAPI community]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FastAPI community
Context triple: [tiangolo, associatedWith, FastAPI community]
  • A. FastAPI chosen
    FastAPI is a modern, high-performance Python framework for building APIs with automatic interactive documentation and type hint–driven validation.
  • B. Uvicorn
    Uvicorn is a high-performance, ASGI-compatible web server implementation for Python, commonly used to run modern async frameworks and applications.
  • C. Python community
    The Python community is the global network of developers, users, and contributors who collaboratively build, maintain, and advance the Python programming language and its ecosystem.
  • D. Pydantic
    Pydantic is a Python library for data validation and settings management that uses type hints to parse, validate, and serialize data.
  • E. Fedora community
    The Fedora community is a global, volunteer-driven group that collaborates to develop, maintain, and promote the Fedora Linux distribution and its related open source projects.
  • 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_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.
Created at: March 12, 2026, 11:07 p.m.