Triple
T33007537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DHCPRELEASE |
E844549
|
entity |
| Predicate | effectOnServer |
P40373
|
FINISHED |
| Object | server may reassign the released IP address |
—
|
LITERAL 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: server may reassign the released IP address | Statement: [DHCPRELEASE, effectOnServer, server may reassign the released IP address]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnServer Context triple: [DHCPRELEASE, effectOnServer, server may reassign the released IP address]
-
A.
effectOnWorld
Indicates how an entity’s actions or existence change, influence, or impact the state of the world.
-
B.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
C.
effectOnSystem
chosen
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
D.
effectOnUsage
Indicates how one factor or condition changes the way something is used, including the extent, manner, or frequency of its usage.
-
E.
effectOnOutput
Indicates how one factor, action, or condition influences or changes the resulting output of a process or system.
- F. None of above.
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_69f3494e59f08190b9127c693e5c7e8f |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 1, 2026, 1:23 a.m.