Triple
T2761802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helvering v. Horst |
E61236
|
entity |
| Predicate | concernedIncomeType |
P24934
|
FINISHED |
| Object | interest coupons from bonds |
—
|
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: interest coupons from bonds | Statement: [Helvering v. Horst, concernedIncomeType, interest coupons from bonds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concernedIncomeType Context triple: [Helvering v. Horst, concernedIncomeType, interest coupons from bonds]
-
A.
incomeType
chosen
Indicates the category or source classification of an entity’s income within a given context.
-
B.
concernsBusinessType
Indicates that something is related or applicable to a particular type or category of business.
-
C.
incomeTreatment
Indicates a relationship where an entity receives, is subject to, or is affected by a particular income-related treatment, policy, or classification.
-
D.
requiresEarnedIncome
Indicates that something is conditional upon an individual or entity having earned income, such as wages or salary, in order to qualify or apply.
-
E.
incomeCounted
Indicates that a specified amount of income is included in a particular calculation, assessment, or determination (such as eligibility, benefits, or totals).
- 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfc5e1c8190a5ac2c48d3eaeb0a |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.