Triple
T37310527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missouri 529 education savings programs |
E926193
|
entity |
| Predicate | investmentOption |
P69262
|
FINISHED |
| Object | age-based portfolios |
—
|
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: age-based portfolios | Statement: [Missouri 529 education savings programs, investmentOption, age-based portfolios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: investmentOption Context triple: [Missouri 529 education savings programs, investmentOption, age-based portfolios]
-
A.
investmentOptions
chosen
Indicates that one entity offers, defines, or is associated with possible ways another entity can allocate resources or capital.
-
B.
investmentType
Indicates the specific category or nature of an investment associated with an entity or transaction.
-
C.
investmentTarget
Indicates that one entity is the object or recipient of another entity’s investment.
-
D.
vestments
Indicates that one entity is wearing or is ceremonially clothed in special religious or official garments associated with a role or office.
-
E.
investment
Indicates a relationship where one party allocates resources (such as money, time, or effort) into something with the expectation of future benefit or return.
- 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_69f76eb1bc508190924e9fa5d8acdeb3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.