Triple
T9313308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-root |
E224056
|
entity |
| Predicate | redundancy |
P51510
|
FINISHED |
| Object | multiple geographically distributed sites |
—
|
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: multiple geographically distributed sites | Statement: [M-root, redundancy, multiple geographically distributed sites]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: redundancy Context triple: [M-root, redundancy, multiple geographically distributed sites]
-
A.
supportsRedundancy
chosen
Indicates that one entity provides or enables backup or failover capabilities for another to ensure continued operation if a primary component fails.
-
B.
reduces
Indicates that one entity causes a decrease in the amount, intensity, degree, or impact of another entity.
-
C.
arity
Indicates the number of arguments or participants that a relation or function takes.
-
D.
reversibility
Indicates that a process, action, or transformation can be undone or reversed to restore the original state or conditions.
-
E.
reusability
Indicates that an entity can be used multiple times or in multiple contexts without significant modification or degradation of function.
- 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_69ca8425f4fc81909c1c586e9a5b7530 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd20b048a081909fd7ec0b6b863063 |
completed | April 1, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:37 p.m.