Triple
T28023509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FAT |
E707749
|
entity |
| Predicate | clusterSizeAffects |
P163634
|
FINISHED |
| Object | storage efficiency |
—
|
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: storage efficiency | Statement: [FAT, clusterSizeAffects, storage efficiency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clusterSizeAffects Context triple: [FAT, clusterSizeAffects, storage efficiency]
-
A.
clusterSizeRange
Indicates the range of allowable or observed sizes for a given cluster within a specified context.
-
B.
clusterConcentration
Indicates how densely the elements within a cluster are packed or distributed relative to one another.
-
C.
clusterDensity
Indicates the degree to which elements within a cluster are closely packed or concentrated relative to its size or volume.
-
D.
clusterShape
Indicates the geometric form or configuration that a cluster of related items or points takes.
-
E.
clusterMass
Indicates the total mass associated with a given cluster, typically aggregating the masses of its constituent elements or members.
- 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_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63c0ccf808190b7184694607fa98a |
completed | May 2, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f63710d17c819084cfe96e6df334fd |
completed | May 2, 2026, 5:40 p.m. |
| PDg | Predicate description generation | batch_69f63893cc188190883ac9321a95d2dc |
completed | May 2, 2026, 5:46 p.m. |
Created at: April 27, 2026, 8:11 p.m.