Triple
T14454173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universal Analytics |
E358409
|
entity |
| Predicate | dataRetentionModel |
P93788
|
FINISHED |
| Object | property-level settings |
—
|
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: property-level settings | Statement: [Universal Analytics, dataRetentionModel, property-level settings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataRetentionModel Context triple: [Universal Analytics, dataRetentionModel, property-level settings]
-
A.
dataRetentionPeriod
chosen
Indicates the length of time data is stored or kept before it is deleted, archived, or otherwise disposed of.
-
B.
retentionMethod
Indicates the method or strategy used to retain or keep something (such as data, customers, or resources) over time.
-
C.
detentionPolicy
Indicates the rules or conditions under which individuals may be held in custody or confinement.
-
D.
preservationPolicy
Indicates the rules or strategy governing how something is maintained, protected, and retained over time.
-
E.
durabilityModel
Indicates a relationship where an entity is associated with a specific model or method used to estimate or characterize its durability over time or under certain conditions.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91a8bf088190abf5fd4f646b8c62 |
completed | April 14, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:19 a.m.