Triple
T7897985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Redis |
E183380
|
entity |
| Predicate | supportsProtocol |
P203
|
FINISHED |
| Object |
RESP
RESP (REdis Serialization Protocol) is a simple, efficient, text-based protocol used by Redis for client-server communication and command serialization.
|
E696499
|
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: RESP | Statement: [Redis, supportsProtocol, RESP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RESP Context triple: [Redis, supportsProtocol, RESP]
-
A.
Res
Res is an American singer-songwriter known for her genre-blending neo-soul and rock-influenced music, particularly her acclaimed early-2000s work.
-
B.
Responder
Responder is a lightweight, high-performance Python web framework designed for building APIs and web applications on top of the ASGI specification.
-
C.
Responder
Responder is a network analysis and credential-harvesting tool commonly used in penetration testing to capture and manipulate authentication traffic on local networks.
-
D.
RES
RES is the abbreviation for Rail Express Systems, a former British Rail sector that specialized in high-speed mail and parcels services.
-
E.
RE
RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
- 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: RESP Triple: [Redis, supportsProtocol, RESP]
Generated description
RESP (REdis Serialization Protocol) is a simple, efficient, text-based protocol used by Redis for client-server communication and command serialization.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RESP Target entity description: RESP (REdis Serialization Protocol) is a simple, efficient, text-based protocol used by Redis for client-server communication and command serialization.
-
A.
Res
Res is an American singer-songwriter known for her genre-blending neo-soul and rock-influenced music, particularly her acclaimed early-2000s work.
-
B.
Responder
Responder is a lightweight, high-performance Python web framework designed for building APIs and web applications on top of the ASGI specification.
-
C.
Responder
Responder is a network analysis and credential-harvesting tool commonly used in penetration testing to capture and manipulate authentication traffic on local networks.
-
D.
RES
RES is the abbreviation for Rail Express Systems, a former British Rail sector that specialized in high-speed mail and parcels services.
-
E.
RE
RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a296db8819084c620b12f77acb5 |
completed | March 31, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bb719a08190a0545a361f559bf7 |
completed | March 31, 2026, 5:29 a.m. |
| NEDg | Description generation | batch_69cb5f1f864c819086d3a2b04061ead0 |
completed | March 31, 2026, 5:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb76aede388190a56e066c3302c35e |
completed | March 31, 2026, 7:24 a.m. |
Created at: March 30, 2026, 5:01 p.m.