Triple
T22191405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interest on Lawyers’ Trust Accounts program |
E548434
|
entity |
| Predicate | benefitsEntity |
P487
|
FINISHED |
| Object | civil legal aid organizations |
—
|
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: civil legal aid organizations | Statement: [Interest on Lawyers’ Trust Accounts program, benefitsEntity, civil legal aid organizations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitsEntity Context triple: [Interest on Lawyers’ Trust Accounts program, benefitsEntity, civil legal aid organizations]
-
A.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
B.
benefits
chosen
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
C.
benefitsState
Indicates that one entity provides an advantage, improvement, or positive outcome to a state or governmental entity.
-
D.
benefitsArea
Indicates that one entity provides advantages, improvements, or positive effects to a specified area or region.
-
E.
benefitAppliesTo
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12ae3e8148190a23decd2dfe24e28 |
completed | April 28, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:35 p.m.