Triple
T13857456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diversity Immigrant Visa |
E333101
|
entity |
| Predicate | feeForEntry |
P3997
|
FINISHED |
| Object | no government fee to submit the initial lottery entry |
—
|
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: no government fee to submit the initial lottery entry | Statement: [Diversity Immigrant Visa, feeForEntry, no government fee to submit the initial lottery entry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: feeForEntry Context triple: [Diversity Immigrant Visa, feeForEntry, no government fee to submit the initial lottery entry]
-
A.
admissionFee
chosen
Indicates the monetary charge required for entry or participation in a place, event, or activity.
-
B.
registrationFee
Indicates the monetary amount required to register for a service, event, or entity.
-
C.
parkingFee
Indicates the monetary charge required for parking a vehicle in a given place or time period.
-
D.
feeType
Indicates the specific category or classification of a fee associated with a transaction, service, or obligation.
-
E.
fareStructure
Indicates the pricing scheme or set of rules that determine how fares are calculated and applied for a given service or trip.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02dc9f488190b7181dcb7e304632 |
completed | April 14, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69dbc8691b608190a25a7c70a366b170 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:14 p.m.