Triple
T22449899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UA |
E554962
|
entity |
| Predicate | associatedWithCompanySector |
P47145
|
FINISHED |
| Object | consumer discretionary |
—
|
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 discretionary | Statement: [UA, associatedWithCompanySector, consumer discretionary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCompanySector Context triple: [UA, associatedWithCompanySector, consumer discretionary]
-
A.
associatedWithEconomicSector
chosen
Indicates that an entity has a connection or involvement with a particular economic sector, such as operating, participating, or being relevant within that sector.
-
B.
associatedCompanyBusinessSegment
Indicates that a company is linked to a specific business segment through its operations, products, or services.
-
C.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
D.
associatedCompanySpecialization
Indicates that a company is linked to a particular area of specialization or expertise.
-
E.
associatedWithCompanySize
Indicates that an entity has a relationship to, or is characterized or categorized by, the size of a company (e.g., small, medium, large).
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4ae8a08190ba6027f036ce62af |
completed | April 29, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69e898ad961c819098fd1e46129bddcc |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:48 p.m.