Triple
T17559702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IPFW |
E427667
|
entity |
| Predicate | hasSubsystem |
P4718
|
FINISHED |
| Object |
dummynet
dummynet is a traffic shaper and network emulator for FreeBSD and related systems, used to simulate and control bandwidth, delay, and packet loss for testing and managing network behavior.
|
E1275583
|
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: dummynet | Statement: [IPFW, hasSubsystem, dummynet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: dummynet Context triple: [IPFW, hasSubsystem, dummynet]
-
A.
TUN
TUN is the three-letter ISO 3166-1 alpha-3 country code assigned to Tunisia.
-
B.
Arpinge
Arpinge is a small rural hamlet in Kent, England, situated in the countryside near Folkestone.
-
C.
NAT
NAT is the station code used to identify Nationaltheatret railway station in Oslo, Norway.
-
D.
NAT
NAT is the IATA airport code for Natal Air Base, a military airfield serving the Natal region in Brazil.
-
E.
DHCP relay agent
A DHCP relay agent is a network device or software component that forwards DHCP messages between clients and servers across different IP subnets, enabling centralized address management in larger networks.
- 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: dummynet Triple: [IPFW, hasSubsystem, dummynet]
Generated description
dummynet is a traffic shaper and network emulator for FreeBSD and related systems, used to simulate and control bandwidth, delay, and packet loss for testing and managing network behavior.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: dummynet Target entity description: dummynet is a traffic shaper and network emulator for FreeBSD and related systems, used to simulate and control bandwidth, delay, and packet loss for testing and managing network behavior.
-
A.
TUN
TUN is the three-letter ISO 3166-1 alpha-3 country code assigned to Tunisia.
-
B.
Arpinge
Arpinge is a small rural hamlet in Kent, England, situated in the countryside near Folkestone.
-
C.
NAT
NAT is the station code used to identify Nationaltheatret railway station in Oslo, Norway.
-
D.
NAT
NAT is the IATA airport code for Natal Air Base, a military airfield serving the Natal region in Brazil.
-
E.
DHCP relay agent
A DHCP relay agent is a network device or software component that forwards DHCP messages between clients and servers across different IP subnets, enabling centralized address management in larger networks.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4562573e48190a19f30fe915a5455 |
completed | April 19, 2026, 4:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01d29694a8819095351b929cfaf324 |
completed | May 11, 2026, 12:59 p.m. |
| NEDg | Description generation | batch_6a01d4436b448190bff8710eac0ce569 |
completed | May 11, 2026, 1:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01d49cb9c081908b07b87ec3b2a133 |
completed | May 11, 2026, 1:07 p.m. |
Created at: April 10, 2026, 5:50 a.m.