Triple
T7428003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syslog |
E171415
|
entity |
| Predicate | hasFacilityRange |
P76953
|
FINISHED |
| Object | 0 to 23 |
—
|
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: 0 to 23 | Statement: [Syslog, hasFacilityRange, 0 to 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacilityRange Context triple: [Syslog, hasFacilityRange, 0 to 23]
-
A.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
B.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
C.
offersCapacityRange
Indicates that an entity provides or makes available a service, product, or resource whose capacity is specified as a range between a minimum and maximum value.
-
D.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
E.
hasTerminalFacility
Indicates that an entity possesses or includes a terminal facility used as an endpoint for transport, communication, or related operations.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f306bfe481909f99f6792de95ffc |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1ee5ab8819091082324f2dc3b8c |
completed | March 27, 2026, 9:09 p.m. |
Created at: March 27, 2026, 3:12 p.m.