Triple
T2606190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Child Maintenance Service |
E58663
|
entity |
| Predicate | enforcementPowers |
P19487
|
FINISHED |
| Object | deduction from earnings orders |
—
|
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: deduction from earnings orders | Statement: [Child Maintenance Service, enforcementPowers, deduction from earnings orders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enforcementPowers Context triple: [Child Maintenance Service, enforcementPowers, deduction from earnings orders]
-
A.
enforcement
Indicates the act of compelling compliance with rules, laws, or agreements through monitoring, pressure, or sanctions.
-
B.
enforcedLaw
Indicates that an authority actively applies or upholds a specific law to regulate behavior or resolve situations.
-
C.
exercisedPowerOver
Indicates that one entity exerted control, influence, or authority over another entity.
-
D.
powers
Indicates that one entity supplies or provides the energy, authority, or driving force that enables another entity to function or operate.
-
E.
exerciseOfPower
chosen
Indicates the exertion or application of authority, control, or influence by one entity over another or within a given 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd80ab7248190ba06ba14fe4c5638 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:49 p.m.