Triple
T9301902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | easyOffice |
E223782
|
entity |
| Predicate | hasBrandConcept |
P87955
|
FINISHED |
| Object | no-frills office services |
—
|
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: no-frills office services | Statement: [easyOffice, hasBrandConcept, no-frills office services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandConcept Context triple: [easyOffice, hasBrandConcept, no-frills office services]
-
A.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
-
B.
hasBrandType
Indicates that an entity is associated with or categorized under a particular brand type or classification.
-
C.
parentBrand
Indicates that one brand is the overarching or owning brand from which another brand is derived or subordinated.
-
D.
hasBrandIdentityElement
Indicates that an entity includes or is associated with a specific component of its overall brand identity (such as a logo, color scheme, or tagline).
-
E.
usedBrand
Indicates that an entity has utilized, applied, or operated a particular brand in some context.
- F. None of above. chosen
Provenance (4 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_69ca8424d0f08190831e2e93c6533aeb |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08d34c4c819095a213360747c3a6 |
completed | April 1, 2026, noon |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:36 p.m.