Triple
T8536207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KONE |
E202082
|
entity |
| Predicate | customerSegments |
P481
|
FINISHED |
| Object | residential buildings |
—
|
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: residential buildings | Statement: [KONE, customerSegments, residential buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: customerSegments Context triple: [KONE, customerSegments, residential buildings]
-
A.
customerGroup
Indicates a relationship in which an entity belongs to, is classified under, or is associated with a particular group of customers.
-
B.
targetMarket
chosen
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
C.
brandSegment
Indicates the specific market segment or customer group that a brand is targeted toward or associated with.
-
D.
marketSegmentCoverage
Indicates the extent to which a product, service, or campaign reaches or serves the intended market segment(s).
-
E.
customerFocus
Indicates that one entity prioritizes understanding and meeting the needs, preferences, or satisfaction of another entity (typically a customer or client).
- 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_69ca832355b08190b8b6a4ab4a4a3554 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6a3f024819095d560a205ff1c75 |
completed | March 31, 2026, 3:22 p.m. |
| PD | Predicate disambiguation | batch_69cbd111bf988190be98c92a607c6456 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:18 p.m.