Triple
T1015830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siebel Systems |
E21926
|
entity |
| Predicate | customerFocus |
P23437
|
FINISHED |
| Object | sales automation |
—
|
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: sales automation | Statement: [Siebel Systems, customerFocus, sales automation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: customerFocus Context triple: [Siebel Systems, customerFocus, sales automation]
-
A.
brandFocus
Indicates that a brand primarily concentrates its efforts, messaging, or resources on a particular target, theme, or market segment.
-
B.
customerType
Indicates the classification or category assigned to a customer based on their characteristics, status, or relationship with a business.
-
C.
majorCustomer
Indicates that one entity is a primary or high-value customer of another entity, typically contributing a significant portion of business or revenue.
-
D.
exportCustomer
Indicates initiating the transfer or output of customer-related data from one system or context to another, typically for integration, backup, or reporting purposes.
-
E.
businessModelFocus
Indicates that one entity’s business model is centered on, tailored to, or primarily oriented around another entity or specific focus area.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7c1e9d08190baf7e81f3777168d |
completed | March 1, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69a4b7238d4c8190b22d6c2ac0ac4911 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7a0d0308190a00192aa9062bdaa |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:41 p.m.