Triple
T19719536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Willinger |
E473566
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
On the Self-Similar Nature of Ethernet Traffic
"On the Self-Similar Nature of Ethernet Traffic" is a landmark research paper that revealed and analyzed the fractal-like, long-range dependent behavior of Ethernet network traffic, fundamentally influencing modern network modeling and performance analysis.
|
E1391359
|
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: On the Self-Similar Nature of Ethernet Traffic | Statement: [Walter Willinger, notableWork, On the Self-Similar Nature of Ethernet Traffic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: On the Self-Similar Nature of Ethernet Traffic Context triple: [Walter Willinger, notableWork, On the Self-Similar Nature of Ethernet Traffic]
-
A.
Self-Similarity in High-Speed Packet Traffic
"Self-Similarity in High-Speed Packet Traffic" is a seminal research paper that revealed and analyzed the self-similar, long-range dependent nature of network traffic, fundamentally changing how Internet traffic is modeled and understood.
-
B.
On the Validity of Poisson Models for Network Traffic
"On the Validity of Poisson Models for Network Traffic" is a highly influential research paper that critically examines and challenges the traditional use of Poisson processes to model Internet and network traffic, highlighting the importance of self-similarity and long-range dependence.
-
C.
Congestion Avoidance and Control (SIGCOMM 1988)
Congestion Avoidance and Control (SIGCOMM 1988) is Van Jacobson’s seminal paper that introduced key TCP congestion control algorithms, fundamentally improving Internet stability and performance.
-
D.
The Addition of Explicit Congestion Notification (ECN) to IP
The Addition of Explicit Congestion Notification (ECN) to IP is an IETF standard (RFC 3168) that specifies how IP and TCP can signal and respond to network congestion without relying solely on packet loss.
-
E.
An Introduction to Queueing Networks
An Introduction to Queueing Networks is a foundational textbook by Jean Walrand that systematically presents the theory, modeling, and analysis of queueing networks in operations research and computer and communication systems.
- 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: On the Self-Similar Nature of Ethernet Traffic Triple: [Walter Willinger, notableWork, On the Self-Similar Nature of Ethernet Traffic]
Generated description
"On the Self-Similar Nature of Ethernet Traffic" is a landmark research paper that revealed and analyzed the fractal-like, long-range dependent behavior of Ethernet network traffic, fundamentally influencing modern network modeling and performance analysis.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: On the Self-Similar Nature of Ethernet Traffic Target entity description: "On the Self-Similar Nature of Ethernet Traffic" is a landmark research paper that revealed and analyzed the fractal-like, long-range dependent behavior of Ethernet network traffic, fundamentally influencing modern network modeling and performance analysis.
-
A.
Self-Similarity in High-Speed Packet Traffic
chosen
"Self-Similarity in High-Speed Packet Traffic" is a seminal research paper that revealed and analyzed the self-similar, long-range dependent nature of network traffic, fundamentally changing how Internet traffic is modeled and understood.
-
B.
On the Validity of Poisson Models for Network Traffic
"On the Validity of Poisson Models for Network Traffic" is a highly influential research paper that critically examines and challenges the traditional use of Poisson processes to model Internet and network traffic, highlighting the importance of self-similarity and long-range dependence.
-
C.
Congestion Avoidance and Control (SIGCOMM 1988)
Congestion Avoidance and Control (SIGCOMM 1988) is Van Jacobson’s seminal paper that introduced key TCP congestion control algorithms, fundamentally improving Internet stability and performance.
-
D.
The Addition of Explicit Congestion Notification (ECN) to IP
The Addition of Explicit Congestion Notification (ECN) to IP is an IETF standard (RFC 3168) that specifies how IP and TCP can signal and respond to network congestion without relying solely on packet loss.
-
E.
An Introduction to Queueing Networks
An Introduction to Queueing Networks is a foundational textbook by Jean Walrand that systematically presents the theory, modeling, and analysis of queueing networks in operations research and computer and communication systems.
- F. None of above.
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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e64410e5548190b60e13603b6c0053 |
completed | April 20, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07b4ec24548190826f8dc75f1de8b7 |
completed | May 16, 2026, 12:06 a.m. |
| NEDg | Description generation | batch_6a07b7600d788190821ed051d074c190 |
completed | May 16, 2026, 12:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07b7c789688190aed9fabf4c68fe1b |
completed | May 16, 2026, 12:18 a.m. |
Created at: April 10, 2026, 1:46 p.m.