Triple

T13636891
Position Surface form Disambiguated ID Type / Status
Subject Active Queue Management E325871 entity
Predicate hasExample P1259 FINISHED
Object BLUE queue management algorithm E325872 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: BLUE queue management algorithm | Statement: [Active Queue Management, hasExample, BLUE queue management algorithm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BLUE queue management algorithm
Context triple: [Active Queue Management, hasExample, BLUE queue management algorithm]
  • A. Priority-based Flow Control
    Priority-based Flow Control is an Ethernet link-layer mechanism that enables lossless data transmission for selected traffic classes by pausing specific priorities instead of the entire link.
  • B. Queueing Systems, Volume 1: Theory
    Queueing Systems, Volume 1: Theory is a foundational textbook by Leonard Kleinrock that rigorously develops the mathematical theory of queueing processes and their applications in communication and computer systems.
  • C. Active Queue Management
    Active Queue Management is a set of techniques used in network routers and switches to proactively manage packet queues and reduce congestion by intelligently dropping or marking packets before buffers overflow.
  • D. Random Early Detection chosen
    Random Early Detection is a congestion avoidance mechanism for packet-switched networks that probabilistically drops packets before a queue becomes full to signal and control incipient congestion.
  • E. IEEE 802.1Qch cyclic queuing and forwarding standard
    The IEEE 802.1Qch cyclic queuing and forwarding standard is a Time-Sensitive Networking (TSN) specification that defines cyclic transmission mechanisms in Ethernet bridges to provide deterministic, low-latency, and low-jitter packet delivery for real-time applications.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a616dc81908b8c1213e1d4beed completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78af297008190b12256c936714213 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:51 p.m.