Triple
T18974573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FirstOntario Credit Union |
E464259
|
entity |
| Predicate | profitOrientation |
P38749
|
FINISHED |
| Object | not-for-profit |
—
|
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: not-for-profit | Statement: [FirstOntario Credit Union, profitOrientation, not-for-profit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: profitOrientation Context triple: [FirstOntario Credit Union, profitOrientation, not-for-profit]
-
A.
profitsFrom
Indicates that one entity gains financial or material benefit as a result of another entity’s actions, existence, or situation.
-
B.
commercialObjective
chosen
Indicates that an action, plan, or entity is primarily intended to achieve commercial or business-related goals, such as generating revenue, profit, or market advantage.
-
C.
viewsProfitAs
Indicates that one entity regards or interprets another entity as a form or source of profit.
-
D.
marketOrientation
Indicates the degree to which an entity’s decisions, strategies, or behaviors are guided by understanding and responding to market conditions, customer needs, and competitor actions.
-
E.
economicGoal
Indicates that an entity has a targeted economic outcome or objective it aims to achieve.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d61e71988190817cada25672a1ce |
completed | April 20, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, noon