Triple
T4177335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life's Good |
E86508
|
entity |
| Predicate | usedByIndustry |
P8461
|
FINISHED |
| Object | consumer electronics industry |
—
|
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: consumer electronics industry | Statement: [Life's Good, usedByIndustry, consumer electronics industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByIndustry Context triple: [Life's Good, usedByIndustry, consumer electronics industry]
-
A.
usedInIndustry
chosen
Indicates that something is employed or applied within a particular industry or industrial sector.
-
B.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
C.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
D.
areUsedBy
Indicates that certain entities serve as tools, resources, or means that are utilized or employed by other entities.
-
E.
mainlyUses
Indicates that one entity primarily relies on, employs, or utilizes another entity as its main tool, method, resource, or medium.
- 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af07078cb081909f64326b12522410 |
completed | March 9, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69af019155448190b19868583272513f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:45 p.m.