Triple
T1866805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BOOTP |
E34939
|
entity |
| Predicate | addressAllocation |
P33251
|
FINISHED |
| Object | preconfigured on server |
—
|
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: preconfigured on server | Statement: [BOOTP, addressAllocation, preconfigured on server]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressAllocation Context triple: [BOOTP, addressAllocation, preconfigured on server]
-
A.
address
Indicates that one entity directs spoken or written communication specifically to another entity.
-
B.
addresses
Indicates that one entity directs speech, communication, or written correspondence specifically toward another entity.
-
C.
addressMode
Indicates how data or resources are accessed or referenced within a system, such as the method or scheme used to locate them.
-
D.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
E.
addressMappingType
Indicates the specific way in which one address is associated with, translated to, or mapped onto another address or address space.
- F. None of above. chosen
Provenance (4 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_69a88600b2f88190bc09303e68ab517e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb16c09e48190a345c95eab59fd87 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe02c3c819093a4744b476106ca |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb16a6db48190af04012e8ed2269f |
completed | March 7, 2026, 5:02 a.m. |
Created at: March 4, 2026, 7:34 p.m.