Triple

T816308
Position Surface form Disambiguated ID Type / Status
Subject FastAPI E17658 entity
Predicate basedOn P98 FINISHED
Object Starlette
Starlette is a lightweight, high-performance ASGI framework for building asynchronous web applications and services in Python.
E97056 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: Starlette | Statement: [FastAPI, basedOn, Starlette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Starlette
Context triple: [FastAPI, basedOn, Starlette]
  • A. Gillian
    Gillian is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • B. Billie
    Billie is the given name of Billie Joe Armstrong, the American musician best known as the lead vocalist and guitarist of the punk rock band Green Day.
  • C. Theresa
    Theresa is a feminine given name of Greek origin, commonly associated in modern times with figures such as former UK Prime Minister Theresa May.
  • D. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • E. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • 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: Starlette
Triple: [FastAPI, basedOn, Starlette]
Generated description
Starlette is a lightweight, high-performance ASGI framework for building asynchronous web applications and services in Python.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Starlette
Target entity description: Starlette is a lightweight, high-performance ASGI framework for building asynchronous web applications and services in Python.
  • A. Gillian
    Gillian is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • B. Billie
    Billie is the given name of Billie Joe Armstrong, the American musician best known as the lead vocalist and guitarist of the punk rock band Green Day.
  • C. Theresa
    Theresa is a feminine given name of Greek origin, commonly associated in modern times with figures such as former UK Prime Minister Theresa May.
  • D. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • E. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab621d2c819083f10bff4f66c482 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8d1a448190be8494fa2776615a completed March 3, 2026, 11:23 p.m.
NEDg Description generation batch_69a78bd0a1d48190907434a17853dfb1 completed March 4, 2026, 1:33 a.m.
NED2 Entity disambiguation (via description) batch_69a78c3a57d88190a994ed44bcb2d8d1 completed March 4, 2026, 1:34 a.m.
Created at: March 1, 2026, 7:38 p.m.