Triple
T4426006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E-Rate program |
E95210
|
entity |
| Predicate | discountBasis |
P6447
|
FINISHED |
| Object | level of poverty of the population served |
—
|
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: level of poverty of the population served | Statement: [E-Rate program, discountBasis, level of poverty of the population served]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: discountBasis Context triple: [E-Rate program, discountBasis, level of poverty of the population served]
-
A.
calculationBasis
chosen
Indicates the rule, method, or reference standard used as the foundation for performing a calculation in the relationship.
-
B.
fareBasis
Indicates the specific fare rule or pricing category that applies to a ticket or travel segment.
-
C.
fareDiscount
Indicates that a reduced price is applied to a standard fare for a product or service.
-
D.
commissionType
Indicates the specific kind or category of commission arrangement that applies to a given transaction or relationship.
-
E.
automaticBidBasis
Indicates that one entity’s bid amount is determined automatically based on a specified rule, condition, or reference value relative to another entity.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3554e40ec8190982acc0948da2f42 |
completed | March 13, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69b34f5eabe88190a12b244ea71e46d6 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:30 p.m.