Triple
T4276404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASGI |
E97055
|
entity |
| Predicate | usedByFramework |
P8459
|
FINISHED |
| Object |
Responder
Responder is a lightweight, high-performance Python web framework designed for building APIs and web applications on top of the ASGI specification.
|
E426644
|
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: Responder | Statement: [ASGI, usedByFramework, Responder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Responder Context triple: [ASGI, usedByFramework, Responder]
-
A.
Responder
Responder is a network analysis and credential-harvesting tool commonly used in penetration testing to capture and manipulate authentication traffic on local networks.
-
B.
Respond/React
"Respond/React" is a track by Malik B., the late Philadelphia rapper best known as a founding member and key early lyricist of The Roots.
-
C.
The Response
The Response is a prominent sculptural group at Canada's National War Memorial in Ottawa, symbolizing the nation's sacrifice and commitment in times of war.
-
D.
RE
RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
-
E.
RE
RE is the abbreviation for RegioExpress, a category of regional express trains commonly used in European rail transport.
- 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: Responder Triple: [ASGI, usedByFramework, Responder]
Generated description
Responder is a lightweight, high-performance Python web framework designed for building APIs and web applications on top of the ASGI specification.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Responder Target entity description: Responder is a lightweight, high-performance Python web framework designed for building APIs and web applications on top of the ASGI specification.
-
A.
Responder
Responder is a network analysis and credential-harvesting tool commonly used in penetration testing to capture and manipulate authentication traffic on local networks.
-
B.
Respond/React
"Respond/React" is a track by Malik B., the late Philadelphia rapper best known as a founding member and key early lyricist of The Roots.
-
C.
The Response
The Response is a prominent sculptural group at Canada's National War Memorial in Ottawa, symbolizing the nation's sacrifice and commitment in times of war.
-
D.
RE
RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
-
E.
RE
RE is the two-letter ISO 3166-1 alpha-2 country code assigned to the French overseas department and region of Réunion.
- 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.