Triple
T28561490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Office Professional Plus 2019 |
E722555
|
entity |
| Predicate | featureLevelComparedToStandard |
P28765
|
FINISHED |
| Object | more advanced |
—
|
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: more advanced | Statement: [Microsoft Office Professional Plus 2019, featureLevelComparedToStandard, more advanced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureLevelComparedToStandard Context triple: [Microsoft Office Professional Plus 2019, featureLevelComparedToStandard, more advanced]
-
A.
featureLevelComparedTo
chosen
Indicates a comparative relationship between entities based on their feature level, specifying how one entity’s feature level ranks relative to another’s.
-
B.
technologyLevelComparedTo
Indicates how the technological advancement of one entity compares relative to that of another entity.
-
C.
technologyLevelComparedToPredecessor
Indicates how the technology level of an entity compares to that of its immediate predecessor.
-
D.
comparisonLevel
Indicates the degree or intensity to which two or more entities are being compared within a given context.
-
E.
architectureLevel
Indicates the relative layer or tier an entity occupies within an architectural structure or system design.
- 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_69f01a5f69d08190ad5c0d2167078dec |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: April 28, 2026, 4:05 a.m.