Triple
T15242738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CareerBuilder (stake) |
E364298
|
entity |
| Predicate | underlyingBusinessSector |
P100108
|
FINISHED |
| Object | online recruitment |
—
|
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: online recruitment | Statement: [CareerBuilder (stake), underlyingBusinessSector, online recruitment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: underlyingBusinessSector Context triple: [CareerBuilder (stake), underlyingBusinessSector, online recruitment]
-
A.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
B.
industryOfUnderlyingCompany
Indicates the industry sector in which the underlying company associated with this entity operates.
-
C.
sectorOfOperation
chosen
Indicates the industry, domain, or field within which an entity conducts its primary activities or operations.
-
D.
associatedWithEconomicSector
Indicates that an entity has a connection or involvement with a particular economic sector, such as operating, participating, or being relevant within that sector.
-
E.
economicSectorDominant
Indicates that one economic sector holds a leading or controlling position relative to others in terms of influence, output, or importance.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007dcc33081908545ea1a1d2c19fe |
completed | April 15, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:13 a.m.