Triple
T9897775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenovo IdeaPad Yoga 11 |
E182217
|
entity |
| Predicate | usageMode |
P11331
|
FINISHED |
| Object | laptop mode |
—
|
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: laptop mode | Statement: [Lenovo IdeaPad Yoga 11, usageMode, laptop mode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageMode Context triple: [Lenovo IdeaPad Yoga 11, usageMode, laptop mode]
-
A.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
usagePattern
Indicates how something is typically used or the recurring manner in which it is employed or consumed.
-
C.
usedOnMode
chosen
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
D.
usageInstruction
Indicates that one entity provides guidance or directions on how to properly use, operate, or handle another entity.
-
E.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4ac27d88190b8255f7e616f95c9 |
completed | April 2, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69cd1d872d50819096b7ab166a8decf1 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:40 p.m.