Triple
T22819395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XG-PON |
E565185
|
entity |
| Predicate | maximumSplitRatio |
P149863
|
FINISHED |
| Object | 1:128 |
—
|
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: 1:128 | Statement: [XG-PON, maximumSplitRatio, 1:128]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumSplitRatio Context triple: [XG-PON, maximumSplitRatio, 1:128]
-
A.
maximumNumberOfSegments
Indicates the greatest allowable or observed count of discrete segments into which something can be or is divided.
-
B.
maximumClusterCount
Indicates the highest number of clusters that are allowed or can be formed in a given context.
-
C.
maximumSegmentLength
Indicates the greatest allowable or observed length of a segment within a given context or structure.
-
D.
representationRatio
Indicates the proportional relationship between how much one entity represents, depicts, or stands in for another relative to some whole or reference amount.
-
E.
canBeSplitAmong
Indicates that something is divisible into parts that can be distributed among multiple recipients or groups.
- 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dcf39a88190bec26affc304236d |
completed | April 29, 2026, 3:41 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:33 p.m.