Triple
T12589848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Livelihood Collection |
E300573
|
entity |
| Predicate | usesBusinessApproach |
P10363
|
FINISHED |
| Object | profit for purpose |
—
|
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: profit for purpose | Statement: [Livelihood Collection, usesBusinessApproach, profit for purpose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBusinessApproach Context triple: [Livelihood Collection, usesBusinessApproach, profit for purpose]
-
A.
usesBusinessModel
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
-
B.
usesBusinessSystem
Indicates that one entity makes use of a particular business system to perform its operations, processes, or functions.
-
C.
includesApproach
chosen
Indicates that one entity incorporates, utilizes, or is characterized by a particular method, strategy, or approach in relation to another entity or context.
-
D.
industryApproach
Indicates the method, strategy, or way in which an industry addresses, handles, or engages with a particular subject or activity.
-
E.
approaches
Indicates that one entity moves closer in position or state to another entity or reference point.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5:06 p.m.